Note
Go to the end to download the full example code.
Combine many specifications: assisted specification algorithm¶
We combine many specifications, defined in Combination of many specifications. This leads to a total of 432 specifications. The algorithm implemented in the AssistedSpecification object is used to investigate some of these specifications. See Bierlaire and Ortelli (2023).
Michel Bierlaire, EPFL Sun Apr 27 2025, 15:59:08
import biogeme.biogeme_logging as blog
from IPython.core.display_functions import display
from biogeme.assisted import AssistedSpecification
from biogeme.biogeme import BIOGEME
from biogeme.multiobjectives import loglikelihood_dimension
from biogeme.results_processing import EstimationResults, compile_estimation_results
from everything_spec import database, model_catalog
logger = blog.get_screen_logger(level=blog.INFO)
logger.info('Example b07everything_assisted')
PARETO_FILE_NAME = 'b07everything_assisted.pareto'
Example b07everything_assisted
Function verifying that the estimation results are valid.
def validity(results: EstimationResults) -> tuple[bool, str | None]:
"""Function verifying that the estimation results are valid.
The results are not valid if any of the time or cost coefficient is non-negative.
"""
for parameter_index, parameter_name in enumerate(results.beta_names):
parameter_value = results.beta_values[parameter_index]
if 'TIME' in parameter_name and parameter_value >= 0:
return False, f'{parameter_name} = {parameter_value}'
if 'COST' in parameter_name and parameter_value >= 0:
return False, f'{parameter_name} = {parameter_value}'
return True, None
Create the Biogeme object
the_biogeme = BIOGEME(database, model_catalog, generate_html=False, generate_yaml=False)
the_biogeme.model_name = 'b07everything'
Biogeme parameters read from biogeme.toml.
Estimate the parameters using assisted specification algorithm.
assisted_specification = AssistedSpecification(
biogeme_object=the_biogeme,
multi_objectives=loglikelihood_dimension,
pareto_file_name=PARETO_FILE_NAME,
validity=validity,
)
non_dominated_models = assisted_specification.run()
Pareto set initialized from file with 431 elements [14 Pareto] and 1 invalid elements.
Biogeme parameters read from biogeme.toml.
Model with 4 unknown parameters [max: 50]
*** Estimate b07everything_000000
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time b_cost asc_car Function Relgrad Radius Rho
0 -0.76 -0.77 -0.7 -0.29 8.8e+03 0.04 10 1.1 ++
1 -0.66 -1.2 -0.77 -0.0015 8.7e+03 0.0064 1e+02 1.1 ++
2 -0.65 -1.3 -0.79 0.016 8.7e+03 0.00012 1e+03 1 ++
3 -0.65 -1.3 -0.79 0.016 8.7e+03 4e-08 1e+03 1 ++
default_specification=asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear
The number of possible specifications [432] exceeds the maximum number [100]. A heuristic algorithm is applied.
*** VNS ***
asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear [8670.163118523758, 4]
Initial pareto: 14
Attempt 0/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000001
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 -0.69 -0.072 1.3 -0.47 -0.52 -0.11 -0.56 -0.65 -0.088 9e+03 0.06 10 0.95 ++
1 -1 -0.69 -0.072 1.3 -0.47 -0.52 -0.11 -0.56 -0.65 -0.088 9e+03 0.06 5 -2.8e+05 -
2 -1 -0.69 -0.072 1.3 -0.47 -0.52 -0.11 -0.56 -0.65 -0.088 9e+03 0.06 2.5 -27 -
3 -1 -0.69 -0.072 1.3 -0.47 -0.52 -0.11 -0.56 -0.65 -0.088 9e+03 0.06 1.2 -1.5 -
4 -0.55 -1.6 -0.25 0.092 -0.78 -1.5 -0.21 0.02 -1.5 -0.16 8.6e+03 0.039 1.2 0.8 +
5 0.012 -2.7 -0.46 0.55 -0.8 -1.9 -0.47 0.14 -1.4 -0.27 8.5e+03 0.012 1.2 0.68 +
6 -0.098 -2.7 -0.56 0.27 -0.79 -1.7 -0.69 0.12 -1.5 -0.26 8.5e+03 0.0014 12 1.1 ++
7 -0.13 -2.6 -0.56 0.22 -0.79 -1.6 -0.63 0.096 -1.4 -0.23 8.5e+03 0.00018 1.2e+02 1 ++
8 -0.13 -2.6 -0.56 0.22 -0.79 -1.6 -0.63 0.096 -1.4 -0.23 8.5e+03 3.8e-07 1.2e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 5 unknown parameters [max: 50]
*** Estimate b07everything_000002
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time lambda_travel_t b_cost asc_car Function Relgrad Radius Rho
0 -0.66 -1 1.6 -0.57 -0.29 8.9e+03 0.045 1 0.83 +
1 -0.57 -1.7 0.55 -0.94 -0.0006 8.7e+03 0.021 1 0.89 +
2 -0.48 -1.6 0.55 -0.78 0.14 8.6e+03 0.00087 10 0.97 ++
3 -0.48 -1.6 0.55 -0.78 0.14 8.6e+03 3.5e-06 10 1 ++
Considering neighbor 1/20 for current solution
Attempt 1/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000003
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost mu_public asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 -0.54 -
1 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 5 1.1 ++
2 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 2.5 1.1 -
3 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 1.2 1.1 -
4 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.62 -5.2 -
5 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.31 -5 -
6 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.16 -4.6 -
7 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.078 -3.1 -
8 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.039 -3.2 -
9 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.02 -3.8 -
10 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.0098 -4.4 -
11 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.0049 -5 -
12 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.0024 -4 -
13 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.0012 -2.4 -
14 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.00061 -1.2 -
15 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.00031 -0.13 -
16 -0.5 -0.39 -0.016 -0.5 -0.5 0.00031 -0.00031 -0.11 1 0.021 -0.017 -0.0052 9e+03 2.4 0.00031 0.67 +
17 -0.5 -0.39 -0.016 -0.5 -0.5 0.00061 -0.00024 -0.11 1 0.021 -0.017 -0.0053 9e+03 1.1 0.00031 0.8 +
18 -0.5 -0.39 -0.016 -0.5 -0.5 0.00092 -0.00026 -0.11 1 0.021 -0.017 -0.0053 9e+03 0.087 0.0031 1 ++
19 -0.5 -0.39 -0.016 -0.5 -0.5 0.004 -0.00027 -0.11 1 0.02 -0.018 -0.0053 9e+03 0.37 0.031 1 ++
20 -0.51 -0.38 -0.016 -0.52 -0.51 0.034 -0.00041 -0.13 1 0.017 -0.025 -0.0059 9e+03 0.16 0.31 1 ++
21 -0.54 -0.24 -0.015 -0.63 -0.54 0.11 -0.00075 -0.43 1 0.023 -0.089 -0.015 8.7e+03 0.58 3.1 0.99 ++
22 -0.54 -0.24 -0.015 -0.63 -0.54 0.11 -0.00075 -0.43 1 0.023 -0.089 -0.015 8.7e+03 0.58 1.5 -90 -
23 -0.54 -0.24 -0.015 -0.63 -0.54 0.11 -0.00075 -0.43 1 0.023 -0.089 -0.015 8.7e+03 0.58 0.76 -28 -
24 -0.54 -0.24 -0.015 -0.63 -0.54 0.11 -0.00075 -0.43 1 0.023 -0.089 -0.015 8.7e+03 0.58 0.38 -1.2 -
25 -0.61 0.026 -0.01 -0.77 -0.56 -0.0047 -0.00024 -0.82 1.2 0.074 -0.17 -0.034 8.6e+03 0.59 0.38 0.88 +
26 -0.7 0.41 0.024 -1 -0.69 -0.062 -1.9e-05 -0.82 1.3 0.019 -0.22 -0.075 8.5e+03 4.4 3.8 1 ++
27 -0.88 0.67 0.67 -1.4 -0.73 -0.096 0.00018 -0.83 1.2 0.13 -0.15 -0.5 8.4e+03 7 38 1.1 ++
28 -1 0.77 0.66 -1.6 -0.72 -0.092 0.00011 -0.85 1 0.2 -0.13 -0.53 8.4e+03 16 38 0.75 +
29 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 38 0.33 +
30 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.066 -0.79 -
31 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.033 -1.1 -
32 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.017 -1.1 -
33 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.0083 -1.1 -
34 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.0041 -1 -
35 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.0021 -0.72 -
36 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.001 -0.42 -
37 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.00052 -0.31 -
38 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.00026 -0.27 -
39 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.00013 -0.26 -
40 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 6.5e-05 -0.25 -
41 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 3.2e-05 -0.25 -
42 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00018 -0.84 1 0.23 -0.14 -0.56 8.4e+03 5.8 3.2e-05 0.6 +
43 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00019 -0.84 1 0.23 -0.14 -0.56 8.4e+03 0.54 0.00032 1.1 ++
44 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00019 -0.84 1 0.23 -0.14 -0.56 8.4e+03 0.021 0.0032 1 ++
45 -1.1 0.87 0.69 -1.7 -0.75 -0.1 0.00017 -0.85 1 0.23 -0.14 -0.56 8.4e+03 0.22 0.032 1 ++
46 -1.1 0.87 0.71 -1.7 -0.73 -0.097 0.00016 -0.86 1 0.22 -0.14 -0.57 8.4e+03 0.17 0.32 1 ++
47 -1.2 0.91 0.85 -1.7 -0.73 -0.096 0.00016 -0.85 1 0.2 -0.13 -0.64 8.4e+03 0.026 3.2 1 ++
48 -1.2 0.91 0.85 -1.7 -0.73 -0.096 0.00016 -0.85 1 0.2 -0.13 -0.64 8.4e+03 2.9e-05 32 1 ++
49 -1.2 0.91 0.85 -1.7 -0.73 -0.096 0.00016 -0.85 1 0.2 -0.13 -0.64 8.4e+03 1.9e-05 3.2e+02 1 ++
50 -1.2 0.91 0.85 -1.7 -0.73 -0.096 0.00016 -0.85 1 0.2 -0.13 -0.64 8.4e+03 8.1e-07 3.2e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 2/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000004
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1.1e+04 0.26 0.5 0.0047 -
1 -0.39 0.021 -0.18 -0.008 -0.5 -0.068 1 -0.38 1.3 0.28 -0.0088 -0.053 -0.032 -0.0044 -0.035 9.2e+03 0.12 0.5 0.72 +
2 -0.34 0.25 0.038 -0.0023 -0.76 -0.11 1 -0.47 1.3 -0.22 -0.062 -0.21 -0.13 -0.018 -0.079 8.6e+03 0.049 5 0.93 ++
3 -0.34 0.25 0.038 -0.0023 -0.76 -0.11 1 -0.47 1.3 -0.22 -0.062 -0.21 -0.13 -0.018 -0.079 8.6e+03 0.049 0.85 -0.91 -
4 -0.5 1.1 0.36 0.12 -1.1 -0.35 0.18 -1 1.9 -0.78 -0.46 -0.63 -0.075 -0.12 -0.47 8.3e+03 0.033 0.85 0.72 +
5 -0.61 1.1 0.47 0.34 -1.5 -0.45 0.4 -1 1.2 -0.73 0.013 -1.5 -0.065 -0.55 -0.61 8.2e+03 0.025 0.85 0.81 +
6 -0.61 0.99 0.43 0.4 -1.5 -0.54 0.36 -1.1 1.2 -0.75 -0.066 -0.99 -0.089 -0.51 -0.51 8.2e+03 0.00093 8.5 0.95 ++
7 -0.8 1.1 0.51 0.48 -1.6 -0.57 0.35 -1.1 1 -0.74 -0.016 -1 -0.084 -0.51 -0.49 8.2e+03 0.0032 8.5 0.5 +
8 -0.82 1.2 0.52 0.48 -1.6 -0.57 0.35 -1.1 1.1 -0.74 -0.018 -1 -0.083 -0.51 -0.49 8.2e+03 0.00012 85 1 ++
9 -0.81 1.1 0.51 0.48 -1.6 -0.57 0.35 -1.1 1.1 -0.74 -0.02 -1 -0.083 -0.51 -0.49 8.2e+03 1.8e-05 8.5e+02 1 ++
10 -0.81 1.1 0.51 0.48 -1.6 -0.57 0.35 -1.1 1.1 -0.74 -0.02 -1 -0.083 -0.51 -0.49 8.2e+03 9.7e-10 8.5e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000005
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train lambda_travel_t b_cost mu_public b_time_swissmet asc_car b_time_car Function Relgrad Radius Rho
0 -1 -0.78 1.1 -0.27 1.5 -0.34 -0.21 -0.32 9.2e+03 0.081 1 0.6 +
1 -0.56 -1.4 0.96 -0.6 1 -1.2 -0.16 -0.82 8.6e+03 0.014 10 1 ++
2 -0.57 -1.6 0.8 -0.82 1 -1.2 -0.13 -0.89 8.6e+03 0.012 1e+02 1 ++
3 -0.18 -2.5 0.22 -0.79 1 -1.8 0.072 -1.4 8.5e+03 0.013 1e+03 0.92 ++
4 -0.16 -2.6 0.27 -0.8 1 -1.7 0.079 -1.4 8.5e+03 0.00027 1e+04 1 ++
5 -0.16 -2.6 0.27 -0.8 1 -1.7 0.079 -1.4 8.5e+03 4e-07 1e+04 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000006
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost mu_public asc_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 1.1e+04 0.26 0.5 -0.18 -
1 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 5 1.1 ++
2 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 2.5 1.1 -
3 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 1.2 1.1 -
4 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.62 1.1 -
5 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.31 -4.7 -
6 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.16 -3.1 -
7 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.078 -2.3 -
8 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.039 -2.6 -
9 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.02 -3.4 -
10 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.0098 -4.3 -
11 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.0049 -5.1 -
12 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.0024 -4.4 -
13 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.0012 -2.6 -
14 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.00061 -1.3 -
15 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.00031 -0.2 -
16 -0.5 -0.5 -0.5 0.00031 -0.00031 -0.5 1 0.034 8.9e+03 2.8 0.00031 0.65 +
17 -0.5 -0.5 -0.5 0.00061 -0.00023 -0.5 1 0.034 8.9e+03 1.2 0.00031 0.81 +
18 -0.5 -0.5 -0.5 0.00092 -0.00026 -0.5 1 0.034 8.9e+03 0.15 0.0031 0.99 ++
19 -0.5 -0.5 -0.5 0.004 -0.00026 -0.5 1 0.033 8.9e+03 0.32 0.031 1 ++
20 -0.51 -0.52 -0.51 0.034 -0.00041 -0.5 1 0.031 8.8e+03 0.23 0.31 1 ++
21 -0.59 -0.77 -0.53 0.054 -0.00049 -0.81 1.2 -0.1 8.6e+03 0.37 0.31 0.89 +
22 -0.59 -0.77 -0.53 0.054 -0.00049 -0.81 1.2 -0.1 8.6e+03 0.37 0.15 -1.4 -
23 -0.58 -0.92 -0.63 -0.065 1e-05 -0.83 1.2 -0.099 8.6e+03 1.8 0.15 0.38 +
24 -0.49 -1.1 -0.71 -0.051 -2.7e-05 -0.83 1.2 -0.077 8.6e+03 5 1.5 0.98 ++
25 -0.49 -1.1 -0.71 -0.051 -2.7e-05 -0.83 1.2 -0.077 8.6e+03 5 0.37 -4.7 -
26 -0.45 -1.4 -0.83 -0.11 0.00017 -0.85 1.1 0.072 8.5e+03 20 0.37 0.31 +
27 -0.45 -1.7 -0.8 -0.095 0.00016 -0.86 1 0.14 8.5e+03 7.2 0.37 0.89 +
28 -0.5 -1.6 -0.77 -0.094 0.00014 -0.86 1 0.14 8.5e+03 3.4 0.37 0.81 +
29 -0.51 -1.6 -0.78 -0.094 0.00015 -0.87 1 0.14 8.5e+03 0.083 3.7 1 ++
30 -0.51 -1.6 -0.78 -0.094 0.00015 -0.86 1 0.14 8.5e+03 0.0045 37 1 ++
31 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 1 0.14 8.5e+03 7.8e-06 3.7e+02 1 ++
32 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 1 0.14 8.5e+03 0.0005 3.7e+03 1 ++
33 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 1 0.14 8.5e+03 5.9e-09 3.7e+03 1 ++
Considering neighbor 2/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000007
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost mu_public b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 -0.74 -0.41 1.2 -0.3 1.6 -0.37 -0.19 -0.25 -0.37 -0.25 9.2e+03 0.11 1 0.49 +
1 0 -0.78 -0.65 1.2 -0.74 1.7 -1 -0.62 -0.087 -0.49 -0.8 8.7e+03 0.058 1 0.69 +
2 0.039 -1.3 -0.84 0.49 -0.84 1.4 -1.5 -0.34 -0.0076 -0.81 -0.85 8.5e+03 0.034 10 1.1 ++
3 -0.097 -1.6 -0.96 0.43 -0.87 1.1 -1.5 -0.4 0.021 -0.85 -0.84 8.5e+03 0.018 1e+02 1.3 ++
4 -0.25 -1.8 -1 0.45 -0.85 1 -1.4 -0.39 0.017 -0.84 -0.84 8.4e+03 0.0067 1e+03 1.2 ++
5 -0.29 -1.8 -1 0.43 -0.86 1 -1.4 -0.4 0.041 -0.83 -0.83 8.4e+03 0.0033 1e+04 1 ++
6 -0.18 -2.1 -1.1 0.24 -0.88 1 -1.5 -0.4 0.084 -0.96 -0.91 8.4e+03 0.0011 1e+05 0.98 ++
7 -0.18 -2.1 -1.1 0.25 -0.88 1 -1.5 -0.41 0.081 -0.95 -0.91 8.4e+03 6.7e-06 1e+06 1 ++
8 -0.18 -2.1 -1.1 0.25 -0.88 1 -1.5 -0.41 0.081 -0.95 -0.91 8.4e+03 2e-09 1e+06 1 ++
Considering neighbor 3/20 for current solution
Attempt 3/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000008
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.83 0.043 -1 -0.12 1.1 -0.19 1.4 -0.026 -0.096 9e+03 0.07 1 0.66 +
1 -0.56 1 -1.2 -0.14 0.82 -1 1.5 -0.18 -0.49 8.3e+03 0.017 10 0.91 ++
2 -0.33 1.2 -1.7 -0.63 0.11 -0.69 1.4 0.16 -1.2 8.3e+03 0.019 10 0.5 +
3 -0.67 1.5 -1.7 -0.59 0.26 -0.73 1 0.2 -1.3 8.2e+03 0.011 10 0.82 +
4 -0.82 1.6 -1.6 -0.57 0.34 -0.71 1.1 0.16 -1.2 8.2e+03 0.00036 1e+02 1 ++
5 -0.8 1.6 -1.6 -0.56 0.35 -0.71 1.1 0.15 -1.2 8.2e+03 6.7e-05 1e+03 0.99 ++
6 -0.8 1.6 -1.6 -0.56 0.35 -0.71 1.1 0.15 -1.2 8.2e+03 8e-09 1e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 4/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000009
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.22 -
1 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.5 0.68 +
2 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.25 -10 -
3 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.12 -12 -
4 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.062 -14 -
5 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.031 -21 -
6 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.016 -2.5 -
7 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.16 0.97 ++
8 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.078 -11 -
9 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.039 -10 -
10 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.02 -8.5 -
11 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.0098 -9.1 -
12 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.0049 -4.5 -
13 -0.29 0.02 -0.12 0.011 -0.52 -0.0088 -0.0014 -0.059 0.18 -0.013 -0.043 -0.027 -0.02 -0.01 9.4e+03 2.8 0.0049 0.51 +
14 -0.29 0.022 -0.12 0.011 -0.52 -0.0072 -0.00045 -0.062 0.18 -0.016 -0.044 -0.029 -0.02 -0.015 9.4e+03 0.082 0.0049 0.89 +
15 -0.29 0.024 -0.12 0.011 -0.52 -0.0053 3.6e-05 -0.065 0.18 -0.018 -0.045 -0.03 -0.021 -0.02 9.4e+03 0.12 0.049 1 ++
16 -0.3 0.041 -0.11 0.011 -0.54 0.014 -0.0014 -0.098 0.19 -0.041 -0.057 -0.048 -0.022 -0.069 9.3e+03 2.8 0.049 0.87 +
17 -0.31 0.068 -0.097 0.012 -0.57 0.035 -0.0008 -0.15 0.17 -0.06 -0.073 -0.064 -0.023 -0.11 9.2e+03 0.96 0.49 1 ++
18 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.49 0.64 +
19 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.24 -6.8 -
20 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.12 -7.3 -
21 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.061 -7.6 -
22 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.031 -7.4 -
23 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.015 -4 -
24 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.0076 -2.6 -
25 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.0038 -1.3 -
26 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0025 -0.64 -0.2 -0.11 -0.23 -0.15 -0.038 -0.42 8.8e+03 7.4 0.0038 0.26 +
27 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.038 1.3 ++
28 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.019 -1.1 -
29 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0095 -1.6 -
30 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0048 -1.9 -
31 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0024 -2.2 -
32 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0012 -1.2 -
33 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0006 -0.64 -
34 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0003 0.084 -
35 -0.37 0.35 0.063 0.02 -0.78 0.18 -0.001 -0.64 -0.2 -0.11 -0.23 -0.14 -0.039 -0.41 8.7e+03 1.2 0.003 0.93 ++
36 -0.37 0.35 0.063 0.02 -0.78 0.18 -0.001 -0.64 -0.2 -0.11 -0.23 -0.14 -0.039 -0.41 8.7e+03 0.29 0.03 0.99 ++
37 -0.37 0.36 0.068 0.021 -0.78 0.17 -0.00099 -0.64 -0.23 -0.1 -0.24 -0.14 -0.039 -0.39 8.6e+03 0.05 0.3 1 ++
38 -0.42 0.54 0.15 0.029 -0.84 0.33 -0.0017 -0.68 -0.53 -0.1 -0.31 -0.13 -0.05 -0.43 8.5e+03 0.32 0.3 0.88 +
39 -0.63 0.84 0.21 0.049 -0.9 0.17 -0.00098 -0.72 -0.66 -0.24 -0.45 -0.18 -0.076 -0.51 8.4e+03 0.34 3 0.96 ++
40 -1.4 1.4 0.5 0.53 -1.2 -0.048 -7.2e-05 -0.71 -1.2 -0.48 -0.89 -0.044 -0.33 -0.83 8.3e+03 1.3 30 1.1 ++
41 -1.3 1.4 0.54 0.61 -1.8 -0.066 2.6e-05 -0.73 -1.8 -0.44 -0.99 -0.059 -0.38 -1.3 8.2e+03 4.5 3e+02 1.2 ++
42 -1.3 1.4 0.54 0.61 -1.8 -0.066 2.6e-05 -0.73 -1.8 -0.44 -0.99 -0.059 -0.38 -1.3 8.2e+03 4.5 0.79 -11 -
43 -1.3 1.4 0.54 0.61 -1.8 -0.066 2.6e-05 -0.73 -1.8 -0.44 -0.99 -0.059 -0.38 -1.3 8.2e+03 4.5 0.39 -3.5 -
44 -1.3 1.4 0.54 0.61 -1.8 -0.066 2.6e-05 -0.73 -1.8 -0.44 -0.99 -0.059 -0.38 -1.3 8.2e+03 4.5 0.2 -0.099 -
45 -1.3 1.4 0.56 0.61 -2 -0.1 0.00017 -0.71 -2 -0.42 -0.99 -0.04 -0.39 -1.5 8.2e+03 9 0.2 0.64 +
46 -1.3 1.4 0.57 0.62 -2.2 -0.097 0.00016 -0.76 -2.2 -0.4 -1 -0.081 -0.39 -1.6 8.1e+03 1.5 2 0.98 ++
47 -1 1.4 0.54 0.61 -2.5 -0.11 0.00022 -0.74 -2.4 -0.38 -0.98 -0.081 -0.42 -1.8 8.1e+03 3.2 20 0.9 ++
48 -1 1.4 0.54 0.58 -2.5 -0.11 0.00021 -0.74 -2.4 -0.39 -0.98 -0.08 -0.43 -1.8 8.1e+03 0.073 2e+02 1 ++
49 -1 1.4 0.54 0.58 -2.5 -0.11 0.00021 -0.74 -2.4 -0.39 -0.98 -0.08 -0.44 -1.8 8.1e+03 0.0017 2e+03 1 ++
50 -1 1.4 0.54 0.58 -2.5 -0.11 0.00021 -0.74 -2.4 -0.39 -0.98 -0.08 -0.44 -1.8 8.1e+03 8e-06 2e+04 1 ++
51 -1 1.4 0.54 0.58 -2.5 -0.11 0.00021 -0.74 -2.4 -0.39 -0.98 -0.08 -0.44 -1.8 8.1e+03 4e-07 2e+04 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000010
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost mu_public asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.78 0.096 -0.32 -0.016 -1 -0.58 -0.29 1.8 -0.076 -0.13 -0.12 -0.011 9.8e+03 0.17 1 0.26 +
1 -0.78 0.096 -0.32 -0.016 -1 -0.58 -0.29 1.8 -0.076 -0.13 -0.12 -0.011 9.8e+03 0.17 0.5 -0.4 -
2 -0.3 0.45 0.18 0.0022 -0.65 -0.43 -0.57 1.5 -0.067 -0.22 -0.15 -0.021 8.6e+03 0.1 0.5 0.68 +
3 -0.72 0.9 0.11 0.077 -0.64 -0.33 -0.8 2 -0.24 -0.54 -0.22 -0.087 8.3e+03 0.024 0.5 0.8 +
4 -0.77 0.85 0.19 0.25 -0.73 -0.49 -0.77 1.5 -0.13 -0.95 -0.081 -0.21 8.3e+03 0.008 0.5 0.89 +
5 -0.97 1 0.31 0.36 -0.79 -0.54 -0.77 1.4 -0.042 -1.2 -0.072 -0.53 8.2e+03 0.0028 5 1.2 ++
6 -1.2 1.1 0.4 0.44 -0.84 -0.57 -0.78 1.2 -0.0039 -1.2 -0.067 -0.55 8.2e+03 0.0037 50 1.1 ++
7 -1.3 1.2 0.44 0.48 -0.84 -0.58 -0.78 1.1 0.0042 -1.2 -0.063 -0.54 8.2e+03 0.00042 5e+02 1.1 ++
8 -1.3 1.2 0.45 0.5 -0.85 -0.58 -0.78 1.1 0.0098 -1.2 -0.062 -0.54 8.2e+03 0.00011 5e+03 1 ++
9 -1.3 1.2 0.45 0.5 -0.85 -0.58 -0.78 1.1 0.0098 -1.2 -0.062 -0.54 8.2e+03 4.9e-07 5e+03 1 ++
Considering neighbor 1/20 for current solution
Attempt 5/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000011
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.96 0.38 0.37 -0.88 0.37 -0.7 -0.27 0.015 -0.33 8.7e+03 0.037 10 1.1 ++
1 -1.2 0.77 0.77 -1.2 0.086 -0.77 0.021 -0.077 -0.53 8.6e+03 0.0079 1e+02 1.1 ++
2 -1.4 0.94 0.93 -1.2 -0.06 -0.78 0.045 -0.079 -0.54 8.6e+03 0.00052 1e+03 1 ++
3 -1.4 0.94 0.93 -1.2 -0.06 -0.78 0.045 -0.079 -0.54 8.6e+03 3.5e-06 1e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000012
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.7 0.37 -0.93 -0.57 2 -0.85 -0.29 -0.31 9.2e+03 0.12 1 0.54 +
1 -1.4 1.4 -0.25 -0.47 1.9 -0.66 -0.033 -0.71 8.5e+03 0.032 1 0.87 +
2 -1.6 1.5 -0.59 -0.68 0.88 -0.94 -0.17 -0.89 8.3e+03 0.026 10 0.94 ++
3 -0.88 1.6 -1.4 -0.63 -0.011 -0.75 0.2 -1.2 8.2e+03 0.0062 10 0.56 +
4 -0.86 1.6 -1.5 -0.6 0.35 -0.78 0.22 -1.2 8.2e+03 0.0074 1e+02 0.98 ++
5 -0.94 1.6 -1.3 -0.61 0.38 -0.78 0.16 -1.2 8.2e+03 0.0002 1e+03 0.99 ++
6 -0.94 1.6 -1.3 -0.61 0.38 -0.78 0.16 -1.2 8.2e+03 6.6e-07 1e+03 1 ++
Considering neighbor 1/20 for current solution
Attempt 6/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000013
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -0.72 -
1 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 5 1.1 ++
2 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 2.5 -7 -
3 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 1.2 -5.9 -
4 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.62 -4.6 -
5 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.31 -3.5 -
6 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.16 -2.9 -
7 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.078 -2.9 -
8 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.039 -3.3 -
9 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.02 -3.7 -
10 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0098 -4.2 -
11 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0049 -3.6 -
12 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0024 -2.5 -
13 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0012 -1.7 -
14 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00061 -0.97 -
15 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00031 -0.12 -
16 -0.5 -0.00028 -0.5 -0.02 -0.5 -0.16 0.00031 -0.00031 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 3.8 0.00031 0.68 +
17 -0.5 -0.0002 -0.5 -0.02 -0.5 -0.16 0.00061 -0.00021 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 4 0.00031 0.36 +
18 -0.5 -0.00011 -0.5 -0.02 -0.5 -0.16 0.00092 -0.00027 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 1.7 0.00031 0.77 +
19 -0.5 -2.1e-05 -0.5 -0.02 -0.5 -0.16 0.0012 -0.00026 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 0.23 0.0031 0.98 ++
20 -0.5 0.00086 -0.5 -0.02 -0.5 -0.16 0.0043 -0.00027 -0.14 0.025 -0.079 -0.023 -0.0067 9.2e+03 0.11 0.031 1 ++
21 -0.51 0.0098 -0.49 -0.02 -0.53 -0.17 0.035 -0.0004 -0.15 0.018 -0.084 -0.03 -0.0071 9.1e+03 0.089 0.31 1 ++
22 -0.56 0.24 -0.31 -0.02 -0.83 -0.18 0.22 -0.0012 -0.45 0.011 -0.2 -0.11 -0.017 8.8e+03 1.8 0.31 0.78 +
23 -0.65 0.54 -0.093 -0.016 -0.96 -0.16 0.012 -0.0003 -0.69 0.093 -0.33 -0.13 -0.03 8.5e+03 1.8 0.31 0.8 +
24 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 3.1 1.1 ++
25 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 1.5 -91 -
26 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 0.76 -19 -
27 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 0.38 -0.76 -
28 -1.1 1.2 0.22 0.018 -1.6 -0.3 -0.13 0.00028 -0.72 0.14 -0.6 -0.11 -0.082 8.3e+03 24 0.38 0.42 +
29 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.38 0.68 +
30 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.19 -1.6 -
31 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.095 -0.57 -
32 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.048 -0.15 -
33 -1.1 1.4 0.36 0.071 -2 -0.53 -0.12 0.00022 -0.73 0.17 -0.72 -0.079 -0.12 8.2e+03 48 0.048 0.11 +
34 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.048 0.15 +
35 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.024 -3.1 -
36 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.012 -3.1 -
37 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.006 -2.9 -
38 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.003 -2.8 -
39 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.0015 -2.7 -
40 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.00075 -2.8 -
41 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.00037 -2.8 -
42 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.00019 -2.8 -
43 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 9.3e-05 -1 -
44 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.00021 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 19 9.3e-05 0.63 +
45 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.00022 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 2.8 0.00093 1.1 ++
46 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.00021 -0.74 0.17 -0.75 -0.092 -0.13 8.2e+03 0.055 0.0093 1 ++
47 -1.1 1.5 0.4 0.088 -2 -0.58 -0.11 0.0002 -0.74 0.17 -0.75 -0.087 -0.14 8.2e+03 0.48 0.093 1 ++
48 -1.2 1.5 0.43 0.14 -2 -0.67 -0.11 0.00019 -0.74 0.21 -0.83 -0.08 -0.17 8.2e+03 1.9 0.93 1 ++
49 -1.3 1.5 0.54 0.6 -2 -1.1 -0.11 0.0002 -0.71 0.21 -1.2 -0.077 -0.46 8.1e+03 0.032 9.3 1 ++
50 -1.3 1.5 0.56 0.59 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.064 -0.5 8.1e+03 0.0004 93 1 ++
51 -1.3 1.5 0.55 0.59 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.068 -0.52 8.1e+03 0.00038 9.3e+02 1 ++
52 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 0.00014 9.3e+03 1 ++
53 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 2.6e-05 9.3e+04 1 ++
54 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 9.8e-06 9.3e+05 1 ++
55 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 0.00038 9.3e+06 1 ++
56 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 3.8e-09 9.3e+06 1 ++
Considering neighbor 0/20 for current solution
Attempt 7/100
Biogeme parameters read from biogeme.toml.
Model with 17 unknown parameters [max: 50]
*** Estimate b07everything_000014
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.52 -
1 1e+04 1.3 0.5 0.23 +
2 1e+04 1.3 0.25 0.23 -
3 1e+04 1.3 0.12 0.23 -
4 1e+04 1.3 0.062 -16 -
5 9.7e+03 6.2 0.062 0.57 +
6 9.7e+03 6.2 0.031 -0.039 -
7 9.7e+03 6.2 0.016 0.089 -
8 9.5e+03 1.1 0.016 0.27 +
9 9.5e+03 1.1 0.0078 -0.88 -
10 9.3e+03 0.62 0.078 0.96 ++
11 9.3e+03 0.62 0.039 -1.4 -
12 9.3e+03 0.62 0.02 -1.6 -
13 9.3e+03 0.62 0.0098 -2.2 -
14 9.3e+03 0.62 0.0049 -3 -
15 9.3e+03 0.62 0.0024 -5.3 -
16 9.3e+03 1.4 0.0024 0.77 +
17 9.3e+03 0.15 0.024 1 ++
18 9.3e+03 0.057 0.24 1 ++
19 9e+03 0.99 0.24 0.87 +
20 9e+03 0.99 0.12 0.87 -
21 9e+03 0.99 0.061 -5.5 -
22 9e+03 0.99 0.031 -5.6 -
23 9e+03 0.99 0.015 -6.7 -
24 9e+03 0.99 0.0076 -8.4 -
25 9e+03 0.99 0.0038 -6.2 -
26 9e+03 0.99 0.0019 -3.2 -
27 9e+03 0.99 0.00095 -0.49 -
28 9e+03 0.24 0.0095 0.92 ++
29 9e+03 0.23 0.095 1 ++
30 8.8e+03 0.33 0.95 0.98 ++
31 8.8e+03 0.33 0.48 -1.3 -
32 8.7e+03 4.2 0.48 0.24 +
33 8.4e+03 0.13 0.48 0.67 +
34 8.4e+03 0.13 0.24 -0.45 -
35 8.3e+03 0.033 0.24 0.82 +
36 8.2e+03 1.5 2.4 1.1 ++
37 8.2e+03 24 2.4 0.79 +
38 8.1e+03 31 2.4 0.64 +
39 8.1e+03 31 1.2 -43 -
40 8.1e+03 31 0.6 -11 -
41 8.1e+03 31 0.3 -4.9 -
42 8.1e+03 31 0.15 -3.6 -
43 8.1e+03 31 0.075 -3 -
44 8.1e+03 31 0.037 -2.6 -
45 8.1e+03 31 0.019 -2.4 -
46 8.1e+03 31 0.0093 -2.6 -
47 8.1e+03 31 0.0047 -2.5 -
48 8.1e+03 31 0.0023 -2.6 -
49 8.1e+03 31 0.0012 -2.6 -
50 8.1e+03 31 0.00058 -2.7 -
51 8.1e+03 31 0.00029 -2.7 -
52 8.1e+03 31 0.00015 -2.5 -
53 8.1e+03 31 7.3e-05 -0.91 -
54 8.1e+03 31 3.6e-05 -0.018 -
55 8.1e+03 2.7 3.6e-05 0.76 +
56 8.1e+03 0.12 0.00036 1 ++
57 8.1e+03 0.22 0.0036 1 ++
58 8.1e+03 0.11 0.036 1 ++
59 8.1e+03 6.4 0.036 0.81 +
60 8.1e+03 0.44 0.36 1 ++
61 8.1e+03 0.038 0.36 0.85 +
62 8.1e+03 0.16 3.6 1 ++
63 8.1e+03 0.00081 36 1 ++
64 8.1e+03 2.8e-06 36 1 ++
Considering neighbor 0/20 for current solution
Attempt 8/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000015
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho
0 -0.99 0.55 0.0022 -0.017 -0.95 2 -0.95 -0.79 -0.38 -0.36 -0.34 -0.039 -0.69 8.9e+03 0.071 1 0.7 +
1 -1.4 1.6 0.44 0.084 -1.1 1.3 -0.53 -1.3 -0.002 -0.69 0.12 -0.12 -1 8.4e+03 0.014 10 0.96 ++
2 -1.4 1.6 0.44 0.084 -1.1 1.3 -0.53 -1.3 -0.002 -0.69 0.12 -0.12 -1 8.4e+03 0.014 0.82 -0.8 -
3 -1.2 1.5 0.66 0.32 -1.9 0.45 -0.82 -1.7 0.13 -0.86 -0.051 -0.23 -1.5 8.2e+03 0.006 8.2 1.1 ++
4 -1 1.4 0.53 0.59 -2.3 0.23 -0.73 -1.8 0.17 -0.95 -0.083 -0.44 -1.5 8.2e+03 0.0017 82 1 ++
5 -1 1.4 0.53 0.55 -2.3 0.22 -0.74 -1.7 0.16 -0.95 -0.081 -0.45 -1.5 8.2e+03 1.9e-05 8.2e+02 1 ++
6 -1 1.4 0.53 0.55 -2.3 0.22 -0.74 -1.7 0.16 -0.95 -0.081 -0.45 -1.5 8.2e+03 5.5e-09 8.2e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 9/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000016
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -1.6 -
1 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.24 -
2 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 2.5 1.1 ++
3 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 1.2 -5.9 -
4 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.62 -3.2 -
5 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.31 -1.5 -
6 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.16 -0.075 -
7 -0.35 -0.17 -0.0076 -0.41 -0.26 0.15 -0.003 -0.36 0.19 0.038 -0.0079 -0.0042 0.02 9.2e+03 9 0.16 0.49 +
8 -0.35 -0.17 -0.0076 -0.41 -0.26 0.15 -0.003 -0.36 0.19 0.038 -0.0079 -0.0042 0.02 9.2e+03 9 0.078 0.058 -
9 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.078 0.14 +
10 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.039 -4.3 -
11 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.02 -2.8 -
12 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.0098 -2 -
13 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.0049 -1.2 -
14 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.0024 0.091 -
15 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.024 1 ++
16 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.012 -2.9 -
17 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.0061 -2.3 -
18 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.0031 -1.8 -
19 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.0015 -1.1 -
20 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.00076 -0.26 -
21 -0.36 -0.15 -0.0042 -0.47 -0.27 0.11 -0.001 -0.38 0.11 0.055 -0.015 -0.0088 0.039 9e+03 2.7 0.00076 0.41 +
22 -0.36 -0.15 -0.0042 -0.47 -0.27 0.11 -0.001 -0.38 0.11 0.055 -0.015 -0.0088 0.039 9e+03 2.7 0.00038 -0.86 -
23 -0.36 -0.15 -0.0039 -0.47 -0.27 0.11 -0.00063 -0.38 0.11 0.054 -0.015 -0.0092 0.039 9e+03 4.3 0.00038 0.45 +
24 -0.36 -0.15 -0.0039 -0.47 -0.27 0.11 -0.00084 -0.38 0.11 0.054 -0.015 -0.0092 0.039 9e+03 2.4 0.00038 0.21 +
25 -0.36 -0.15 -0.0039 -0.47 -0.27 0.11 -0.00084 -0.38 0.11 0.054 -0.015 -0.0092 0.039 9e+03 2.4 0.00019 -1.3 -
26 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00065 -0.38 0.11 0.054 -0.015 -0.0094 0.039 9e+03 3.7 0.00019 0.15 +
27 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00077 -0.38 0.11 0.054 -0.015 -0.0094 0.039 8.9e+03 1.4 0.00019 0.62 +
28 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00072 -0.38 0.11 0.054 -0.015 -0.0094 0.04 8.9e+03 0.72 0.00019 0.77 +
29 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00073 -0.38 0.11 0.054 -0.015 -0.0094 0.04 8.9e+03 0.058 0.0019 1 ++
30 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00074 -0.38 0.11 0.054 -0.016 -0.0094 0.04 8.9e+03 0.26 0.019 1 ++
31 -0.37 -0.15 -0.0036 -0.48 -0.28 0.12 -0.00076 -0.39 0.089 0.054 -0.019 -0.01 0.041 8.9e+03 0.056 0.19 1 ++
32 -0.39 -0.095 -0.0027 -0.57 -0.32 0.18 -0.001 -0.46 -0.1 0.049 -0.06 -0.016 0.048 8.8e+03 0.18 1.9 0.99 ++
33 -0.39 -0.095 -0.0027 -0.57 -0.32 0.18 -0.001 -0.46 -0.1 0.049 -0.06 -0.016 0.048 8.8e+03 0.18 0.95 -61 -
34 -0.39 -0.095 -0.0027 -0.57 -0.32 0.18 -0.001 -0.46 -0.1 0.049 -0.06 -0.016 0.048 8.8e+03 0.18 0.48 0.042 -
35 -0.44 0.18 0.0063 -0.77 -0.4 0.073 -0.00057 -0.81 -0.58 -0.2 -0.34 -0.048 -0.11 8.5e+03 0.041 4.8 0.98 ++
36 -0.75 0.64 0.5 -1 -0.52 -0.046 -7.8e-05 -1.5 -0.84 -0.44 -0.095 -0.46 -0.31 8.3e+03 0.24 48 1.2 ++
37 -0.61 0.73 0.6 -1.5 -0.61 -0.09 0.00011 -1.7 -0.88 -0.34 -0.13 -0.53 -0.35 8.3e+03 2.3 4.8e+02 1.3 ++
38 -0.51 0.75 0.62 -1.9 -0.65 -0.11 0.0002 -1.8 -0.89 -0.29 -0.14 -0.58 -0.34 8.2e+03 0.69 4.8e+03 1.1 ++
39 -0.49 0.74 0.59 -1.9 -0.66 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.63 -0.34 8.2e+03 0.006 4.8e+04 0.99 ++
40 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 0.0064 4.8e+05 1 ++
41 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 2.6e-05 4.8e+06 1 ++
42 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 0.00011 4.8e+07 1 ++
43 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 6.3e-07 4.8e+07 1 ++
Considering neighbor 0/20 for current solution
Attempt 10/100
Biogeme parameters read from biogeme.toml.
Model with 6 unknown parameters [max: 50]
*** Estimate b07everything_000017
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time lambda_travel_t b_cost mu_public asc_car Function Relgrad Radius Rho
0 -0.82 -1 1.1 -0.19 1.3 -0.025 9e+03 0.066 1 0.68 +
1 0.18 -1.9 0.13 -0.67 1.4 0.25 8.8e+03 0.015 1 0.59 +
2 -0.14 -1.7 0.39 -0.77 1.2 0.15 8.6e+03 0.0084 10 1.2 ++
3 -0.36 -1.6 0.53 -0.78 1.1 0.12 8.6e+03 0.0026 1e+02 1.1 ++
4 -0.47 -1.6 0.55 -0.79 1 0.13 8.6e+03 0.001 1e+03 1.1 ++
5 -0.47 -1.6 0.55 -0.79 1 0.14 8.6e+03 0.00021 1e+04 1 ++
6 -0.47 -1.6 0.55 -0.79 1 0.14 8.6e+03 2.2e-07 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 11/100
Considering neighbor 0/20 for current solution
Attempt 12/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000018
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 -2.6 -
1 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.25 -0.11 -
2 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 2.5 1 ++
3 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 1.2 1 -
4 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 0.62 1 -
5 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 0.31 -2.2 -
6 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 0.16 -0.21 -
7 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.16 0.32 +
8 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.078 -0.5 -
9 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.039 -0.4 -
10 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.02 -0.35 -
11 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.0098 -0.32 -
12 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.0049 -0.31 -
13 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.0024 0.093 -
14 -0.32 -0.41 0.11 -0.00046 -0.33 1.3 0.22 -0.048 0.25 9e+03 5.3 0.0024 0.69 +
15 -0.32 -0.41 0.11 -0.00046 -0.33 1.3 0.22 -0.048 0.25 9e+03 5.3 0.0012 -1.2 -
16 -0.32 -0.41 0.11 -0.00046 -0.33 1.3 0.22 -0.048 0.25 9e+03 5.3 0.00061 -0.57 -
17 -0.32 -0.41 0.11 -0.00046 -0.33 1.3 0.22 -0.048 0.25 9e+03 5.3 0.00031 -0.014 -
18 -0.32 -0.41 0.11 -0.00076 -0.33 1.3 0.22 -0.049 0.25 9e+03 2.5 0.00031 0.58 +
19 -0.32 -0.41 0.11 -0.00066 -0.33 1.3 0.22 -0.049 0.25 9e+03 2.5 0.00031 0.43 +
20 -0.32 -0.41 0.11 -0.00071 -0.33 1.3 0.22 -0.049 0.25 9e+03 0.18 0.0031 0.96 ++
21 -0.32 -0.41 0.11 -0.00071 -0.33 1.3 0.22 -0.049 0.24 9e+03 0.065 0.031 1 ++
22 -0.32 -0.43 0.12 -0.00077 -0.34 1.3 0.22 -0.049 0.21 9e+03 0.18 0.31 1 ++
23 -0.33 -0.63 0.24 -0.0012 -0.44 1.5 0.17 -0.065 -0.092 8.7e+03 0.083 3.1 0.91 ++
24 -0.33 -0.63 0.24 -0.0012 -0.44 1.5 0.17 -0.065 -0.092 8.7e+03 0.083 1.5 0.91 -
25 -0.33 -0.63 0.24 -0.0012 -0.44 1.5 0.17 -0.065 -0.092 8.7e+03 0.083 0.76 -26 -
26 -0.33 -0.63 0.24 -0.0012 -0.44 1.5 0.17 -0.065 -0.092 8.7e+03 0.083 0.38 -0.89 -
27 -0.18 -0.76 0.027 -0.00036 -0.68 1.7 -0.22 -0.3 -0.41 8.5e+03 0.33 0.38 0.69 +
28 -0.16 -1.1 -0.089 0.00013 -1 2 -0.28 -0.28 -0.58 8.3e+03 0.6 3.8 1 ++
29 0.1 -1.6 -0.091 0.00013 -1.1 2 -0.19 -0.25 -0.6 8.3e+03 2.3 38 1.1 ++
30 0.21 -2 -0.12 0.00024 -1.2 1.8 -0.15 -0.27 -0.63 8.3e+03 6.2 38 0.47 +
31 0.19 -1.9 -0.11 0.00021 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.86 3.8e+02 1.1 ++
32 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.036 3.8e+03 1 ++
33 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.0057 3.8e+04 1 ++
34 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.0087 3.8e+05 1 ++
35 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.00018 3.8e+06 1 ++
36 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.00035 3.8e+07 1 ++
37 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 3.1e-06 3.8e+07 1 ++
Considering neighbor 0/20 for current solution
Attempt 13/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000019
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 -3.1 -
1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.25 -0.54 -
2 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 2.5 1 ++
3 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 1.2 1 -
4 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.62 1 -
5 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.31 1 -
6 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.16 -1.5 -
7 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.078 -0.98 -
8 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.039 -0.97 -
9 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.02 -1.3 -
10 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.0098 -1.8 -
11 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.0049 -2.5 -
12 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.0024 -3.1 -
13 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.0012 -2.7 -
14 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.00061 -1.3 -
15 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.00031 -0.28 -
16 -0.25 -0.25 -0.01 -0.25 -0.082 0.00031 -0.00031 -0.25 1.3 0.014 -0.011 -0.0035 -0.01 0.25 9.3e+03 2.2 0.00031 0.6 +
17 -0.25 -0.25 -0.01 -0.25 -0.082 0.00053 -0.00023 -0.25 1.3 0.014 -0.011 -0.0035 -0.01 0.25 9.3e+03 0.48 0.0031 0.91 ++
18 -0.25 -0.25 -0.01 -0.25 -0.083 0.0027 -0.00025 -0.25 1.3 0.014 -0.011 -0.0035 -0.0096 0.25 9.3e+03 0.081 0.031 1 ++
19 -0.27 -0.25 -0.01 -0.28 -0.088 0.025 -0.00035 -0.27 1.3 0.022 -0.013 -0.0041 -0.0037 0.23 9.2e+03 0.25 0.31 1 ++
20 -0.39 -0.21 -0.012 -0.59 -0.13 0.25 -0.0013 -0.47 1.4 0.078 -0.048 -0.011 0.042 0.026 8.9e+03 5.1 0.31 0.65 +
21 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.31 0.6 +
22 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.15 0.6 -
23 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.076 0.6 -
24 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.038 0.6 -
25 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.019 0.6 -
26 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0095 0.6 -
27 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0048 -1.9 -
28 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0024 -1.6 -
29 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0012 -1 -
30 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0006 -0.41 -
31 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0003 0.07 -
32 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00082 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.7e+03 6 0.0003 0.7 +
33 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00082 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.7e+03 6 0.00015 -0.95 -
34 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00082 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.7e+03 6 7.5e-05 -1.1 -
35 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00075 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.6e+03 6.2 7.5e-05 0.37 +
36 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00078 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.6e+03 0.6 0.00075 0.92 ++
37 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00078 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.6e+03 0.067 0.0075 1 ++
38 -0.21 0.077 -0.0032 -0.66 -0.12 0.13 -0.00079 -0.5 1.5 -0.099 -0.24 -0.028 -0.099 -0.28 8.6e+03 0.33 0.075 1 ++
39 -0.27 0.052 -0.003 -0.7 -0.12 0.15 -0.00088 -0.57 1.5 -0.05 -0.21 -0.03 -0.055 -0.3 8.5e+03 0.047 0.75 1 ++
40 -0.27 0.052 -0.003 -0.7 -0.12 0.15 -0.00088 -0.57 1.5 -0.05 -0.21 -0.03 -0.055 -0.3 8.5e+03 0.047 0.37 -7.1 -
41 -0.37 0.2 0.013 -0.89 -0.098 -0.038 -9.3e-05 -0.95 1.8 -0.1 -0.25 -0.064 -0.11 -0.43 8.4e+03 0.61 0.37 0.89 +
42 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 3.7 0.99 ++
43 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 1.5 -1.6e+02 -
44 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 0.77 -35 -
45 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 0.39 -5.8 -
46 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 0.19 -1.6 -
47 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 0.096 -0.22 -
48 -0.3 0.33 0.068 -1.4 -0.2 -0.11 0.00019 -1 2 -0.21 -0.09 -0.14 -0.28 -0.55 8.2e+03 18 0.096 0.61 +
49 -0.25 0.39 0.085 -1.5 -0.24 -0.09 0.00012 -1 2 -0.2 -0.074 -0.16 -0.26 -0.61 8.2e+03 2.5 0.96 0.98 ++
50 -0.14 0.46 0.26 -1.9 -0.74 -0.12 0.00026 -1.2 1.8 -0.13 -0.065 -0.39 -0.25 -0.63 8.2e+03 19 0.96 0.56 +
51 -0.16 0.51 0.27 -1.9 -0.83 -0.11 0.0002 -1.2 1.7 -0.13 -0.063 -0.47 -0.26 -0.67 8.2e+03 8.9 0.96 0.88 +
52 -0.17 0.51 0.27 -1.9 -0.82 -0.11 0.0002 -1.3 1.7 -0.14 -0.066 -0.5 -0.27 -0.66 8.2e+03 0.28 9.6 1 ++
53 -0.17 0.51 0.26 -1.9 -0.82 -0.11 0.0002 -1.3 1.7 -0.14 -0.068 -0.52 -0.27 -0.66 8.2e+03 0.015 96 1 ++
54 -0.17 0.51 0.26 -1.9 -0.82 -0.11 0.0002 -1.3 1.7 -0.14 -0.068 -0.52 -0.27 -0.66 8.2e+03 3.2e-05 9.6e+02 1 ++
55 -0.17 0.51 0.26 -1.9 -0.82 -0.11 0.0002 -1.3 1.7 -0.14 -0.068 -0.52 -0.27 -0.66 8.2e+03 1e-06 9.6e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000020
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_time_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.4 0.5 -0.29 -
1 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.5 0.73 +
2 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.25 0.73 -
3 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.12 0.73 -
4 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.062 0.73 -
5 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.031 -18 -
6 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.016 -4.3 -
7 -0.26 -0.13 -0.005 -0.49 -0.013 -0.002 -0.054 1.2 -0.0082 -0.022 -0.003 -0.01 0.19 9.4e+03 4.6 0.016 0.61 +
8 -0.26 -0.12 -0.0049 -0.5 -0.012 8.4e-05 -0.064 1.2 -0.015 -0.027 -0.0033 -0.026 0.19 9.3e+03 0.18 0.016 0.83 +
9 -0.27 -0.12 -0.0047 -0.5 -0.0084 -0.00068 -0.076 1.2 -0.022 -0.034 -0.0038 -0.042 0.19 9.3e+03 0.56 0.16 0.96 ++
10 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.16 0.89 +
11 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.078 -6.3 -
12 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.039 -6.4 -
13 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.02 -6.8 -
14 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.0098 -7.3 -
15 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.0049 -6.6 -
16 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.0024 -3.3 -
17 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.0012 -1.3 -
18 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.00061 -0.03 -
19 -0.27 -0.063 -0.002 -0.55 0.036 -0.00047 -0.22 1.3 -0.093 -0.099 -0.0096 -0.2 0.16 9.1e+03 0.59 0.00061 0.76 +
20 -0.27 -0.063 -0.002 -0.55 0.036 -0.00042 -0.22 1.3 -0.093 -0.099 -0.0096 -0.2 0.16 9.1e+03 0.075 0.0061 1 ++
21 -0.27 -0.062 -0.0019 -0.55 0.035 -0.00044 -0.23 1.3 -0.09 -0.098 -0.0097 -0.19 0.15 9.1e+03 0.28 0.061 1 ++
22 -0.27 -0.046 -0.00092 -0.57 0.033 -0.00038 -0.27 1.3 -0.067 -0.091 -0.011 -0.17 0.092 9e+03 0.073 0.61 0.99 ++
23 -0.26 0.23 0.015 -0.73 0.24 -0.0011 -0.83 1.7 -0.05 -0.17 -0.034 -0.34 -0.52 8.6e+03 6 0.61 0.63 +
24 -0.26 0.23 0.015 -0.73 0.24 -0.0011 -0.83 1.7 -0.05 -0.17 -0.034 -0.34 -0.52 8.6e+03 6 0.31 -0.03 -
25 -0.26 0.23 0.015 -0.73 0.24 -0.0011 -0.83 1.7 -0.05 -0.17 -0.034 -0.34 -0.52 8.6e+03 6 0.15 0.068 -
26 -0.29 0.25 0.028 -0.72 0.31 -0.0025 -0.71 1.8 -0.1 -0.16 -0.051 -0.49 -0.59 8.5e+03 5.5 0.15 0.4 +
27 -0.32 0.26 0.036 -0.74 0.15 -0.00082 -0.68 1.8 -0.14 -0.17 -0.062 -0.47 -0.58 8.4e+03 6.9 1.5 1 ++
28 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 1.5 0.47 +
29 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.76 -6.5 -
30 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.38 -1.7 -
31 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.19 -0.94 -
32 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.095 -0.67 -
33 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.048 -0.14 -
34 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.048 0.26 +
35 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.024 0.26 -
36 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.012 0.26 -
37 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.006 0.26 -
38 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.003 -3.7 -
39 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.0015 -2.6 -
40 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.00075 -1.8 -
41 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.00037 -0.82 -
42 -0.63 0.46 0.43 -1.1 -0.083 1e-05 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 21 0.00037 0.45 +
43 -0.63 0.46 0.43 -1.1 -0.083 1e-05 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 21 0.00019 -0.32 -
44 -0.64 0.46 0.43 -1.1 -0.083 0.0002 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 15 0.00019 0.12 +
45 -0.64 0.46 0.43 -1.1 -0.083 0.0002 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 15 9.3e-05 -0.081 -
46 -0.64 0.46 0.43 -1.1 -0.082 0.0001 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 0.51 9.3e-05 0.82 +
47 -0.64 0.46 0.43 -1.1 -0.082 0.0001 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 0.084 0.00093 1 ++
48 -0.64 0.46 0.43 -1.1 -0.081 9.9e-05 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 0.46 0.0093 1 ++
49 -0.64 0.46 0.43 -1.1 -0.072 5.9e-05 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 0.25 0.093 1 ++
50 -0.57 0.51 0.42 -1.2 -0.041 -9.3e-05 -0.59 2.3 -0.43 -0.0075 -0.48 -0.77 -1.2 8.3e+03 6.2 0.93 1 ++
51 -0.57 0.51 0.42 -1.2 -0.041 -9.3e-05 -0.59 2.3 -0.43 -0.0075 -0.48 -0.77 -1.2 8.3e+03 6.2 0.47 -9.2 -
52 -0.57 0.51 0.42 -1.2 -0.041 -9.3e-05 -0.59 2.3 -0.43 -0.0075 -0.48 -0.77 -1.2 8.3e+03 6.2 0.23 -0.38 -
53 -0.52 0.48 0.38 -1.4 -0.097 0.00018 -0.57 2.4 -0.51 0.029 -0.45 -0.89 -1.3 8.3e+03 11 0.23 0.78 +
54 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.23 0.76 +
55 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.12 -0.23 -
56 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.058 -0.15 -
57 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.029 -0.29 -
58 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.015 -0.24 -
59 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.0073 -0.4 -
60 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.0036 -0.42 -
61 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.0018 -0.35 -
62 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.00091 -0.35 -
63 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.00045 -0.35 -
64 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.00023 -0.36 -
65 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.00011 -0.36 -
66 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 5.7e-05 -0.36 -
67 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 2.8e-05 0.019 -
68 -0.43 0.5 0.33 -1.6 -0.086 0.00011 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 1.6 2.8e-05 0.82 +
69 -0.43 0.5 0.33 -1.6 -0.086 0.00011 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 0.02 0.00028 0.99 ++
70 -0.43 0.5 0.33 -1.6 -0.086 0.00012 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 0.022 0.0028 1 ++
71 -0.43 0.5 0.33 -1.6 -0.089 0.00013 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 0.046 0.028 0.99 ++
72 -0.43 0.48 0.33 -1.6 -0.095 0.00016 -0.57 2.5 -0.52 0.017 -0.41 -1 -1.6 8.2e+03 0.33 0.28 0.99 ++
73 -0.28 0.42 0.27 -1.9 -0.11 0.00021 -0.57 2.5 -0.57 0.034 -0.37 -1.2 -1.9 8.2e+03 3.7 2.8 0.93 ++
74 -0.19 0.44 0.24 -2.1 -0.11 0.0002 -0.61 2.3 -0.47 -0.021 -0.39 -1.3 -1.9 8.2e+03 0.07 28 1 ++
75 -0.22 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.019 -0.42 -1.3 -2 8.2e+03 0.0018 2.8e+02 1 ++
76 -0.21 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.02 -0.42 -1.3 -2 8.2e+03 0.00057 2.8e+03 1 ++
77 -0.21 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.02 -0.43 -1.3 -2 8.2e+03 3e-05 2.8e+04 1 ++
78 -0.21 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.02 -0.43 -1.3 -2 8.2e+03 0.00012 2.8e+05 1 ++
79 -0.21 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.02 -0.43 -1.3 -2 8.2e+03 2.4e-06 2.8e+05 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000021
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 0 -
1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.25 -0.39 -
2 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 2.5 1 ++
3 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 1.2 1 -
4 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.62 -4.2 -
5 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.31 -2.6 -
6 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.16 -0.39 -
7 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.16 0.18 +
8 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.078 -0.8 -
9 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.039 -0.7 -
10 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.02 -0.64 -
11 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.0098 -0.59 -
12 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.0049 -0.12 -
13 -0.34 -0.17 -0.0074 -0.41 -0.085 0.12 0.0012 -0.35 1.1 0.22 0.024 -0.013 -0.004 0.0052 9.2e+03 5.2 0.0049 0.32 +
14 -0.34 -0.17 -0.0074 -0.41 -0.085 0.12 0.0012 -0.35 1.1 0.22 0.024 -0.013 -0.004 0.0052 9.2e+03 5.2 0.0024 -0.52 -
15 -0.35 -0.17 -0.005 -0.41 -0.083 0.12 -0.0013 -0.35 1.1 0.22 0.027 -0.016 -0.0065 0.0076 9.1e+03 4.1 0.0024 0.65 +
16 -0.35 -0.17 -0.0049 -0.41 -0.083 0.12 -0.00081 -0.35 1.1 0.22 0.027 -0.016 -0.0065 0.0078 9.1e+03 2.1 0.024 1.4 ++
17 -0.35 -0.16 -0.0048 -0.43 -0.085 0.13 -0.00075 -0.36 1.1 0.19 0.028 -0.019 -0.0071 0.0097 9.1e+03 2.8 0.24 0.96 ++
18 -0.37 -0.085 -0.0034 -0.58 -0.11 0.22 -0.0012 -0.44 1.1 -0.05 0.033 -0.054 -0.013 0.021 8.8e+03 2.5 2.4 0.96 ++
19 -0.37 -0.085 -0.0034 -0.58 -0.11 0.22 -0.0012 -0.44 1.1 -0.05 0.033 -0.054 -0.013 0.021 8.8e+03 2.5 1.2 0.96 -
20 -0.37 -0.085 -0.0034 -0.58 -0.11 0.22 -0.0012 -0.44 1.1 -0.05 0.033 -0.054 -0.013 0.021 8.8e+03 2.5 0.61 -6.1 -
21 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 6.1 0.94 ++
22 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 3.1 0.94 -
23 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 1.5 0.94 -
24 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.76 0.94 -
25 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.38 0.94 -
26 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.19 -5.7 -
27 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.095 -4.4 -
28 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.048 -3.8 -
29 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.024 -3.9 -
30 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.012 -4 -
31 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.006 -4.1 -
32 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.003 -2.4 -
33 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.0015 -1.7 -
34 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.00075 -0.95 -
35 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.00037 -0.38 -
36 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.00019 -0.0023 -
37 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00062 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 5.2 0.00019 0.45 +
38 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00062 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 5.2 9.3e-05 -1.2 -
39 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00052 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 8.2 9.3e-05 0.19 +
40 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00057 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 2.7 9.3e-05 0.66 +
41 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00055 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 1.1 9.3e-05 0.81 +
42 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00056 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 0.043 0.00093 1 ++
43 -0.4 0.35 0.017 -0.93 -0.12 0.072 -0.00056 -0.96 1.3 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 0.16 0.0093 1 ++
44 -0.4 0.35 0.017 -0.94 -0.12 0.077 -0.00058 -0.96 1.3 -0.65 -0.24 -0.35 -0.056 -0.17 8.5e+03 0.033 0.093 1 ++
45 -0.44 0.35 0.024 -0.98 -0.13 0.022 -0.00036 -1.1 1.3 -0.57 -0.26 -0.33 -0.063 -0.19 8.4e+03 0.041 0.93 1 ++
46 -0.44 0.35 0.024 -0.98 -0.13 0.022 -0.00036 -1.1 1.3 -0.57 -0.26 -0.33 -0.063 -0.19 8.4e+03 0.041 0.47 -16 -
47 -0.44 0.35 0.024 -0.98 -0.13 0.022 -0.00036 -1.1 1.3 -0.57 -0.26 -0.33 -0.063 -0.19 8.4e+03 0.041 0.23 -4.4 -
48 -0.4 0.48 0.067 -1.2 -0.21 -0.13 0.00026 -1.3 1.4 -0.58 -0.33 -0.22 -0.095 -0.29 8.4e+03 18 0.23 0.2 +
49 -0.33 0.53 0.1 -1.4 -0.32 -0.059 -7.9e-06 -1.3 1.4 -0.75 -0.34 -0.18 -0.11 -0.33 8.3e+03 4.8 0.23 0.75 +
50 -0.33 0.53 0.1 -1.4 -0.32 -0.059 -7.9e-06 -1.3 1.4 -0.75 -0.34 -0.18 -0.11 -0.33 8.3e+03 4.8 0.12 -0.16 -
51 -0.33 0.52 0.13 -1.6 -0.38 -0.12 0.00023 -1.4 1.4 -0.71 -0.35 -0.16 -0.13 -0.36 8.3e+03 21 0.12 0.31 +
52 -0.25 0.56 0.17 -1.7 -0.47 -0.096 0.00015 -1.4 1.4 -0.77 -0.35 -0.14 -0.15 -0.39 8.3e+03 7 1.2 0.91 ++
53 -0.32 0.72 0.44 -2.2 -0.93 -0.12 0.00024 -1.7 1 -0.83 -0.22 -0.14 -0.47 -0.37 8.3e+03 16 1.2 0.72 +
54 -0.34 0.72 0.46 -2.2 -0.96 -0.11 0.00021 -1.8 1 -0.8 -0.19 -0.13 -0.48 -0.35 8.2e+03 1.9 12 1 ++
55 -0.37 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.19 -0.14 -0.6 -0.37 8.2e+03 0.16 1.2e+02 1 ++
56 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.19 -0.13 -0.63 -0.37 8.2e+03 0.006 1.2e+03 1 ++
57 -0.37 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 6.9e-05 1.2e+04 1 ++
58 -0.37 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 4.8e-06 1.2e+04 1 ++
Considering neighbor 2/20 for current solution
Attempt 14/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000022
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 -1.9 -
1 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.25 0.011 -
2 -0.25 -0.00017 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 2.5 1 ++
3 -0.25 -0.00017 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 1.2 -4.5 -
4 -0.25 -0.00017 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 0.62 -2.8 -
5 -0.25 -0.00017 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 0.31 -1.3 -
6 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.31 0.18 +
7 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.16 -0.25 -
8 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.078 0.05 -
9 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.039 0.092 -
10 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.02 0.076 -
11 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.0098 0.054 -
12 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.0049 0.037 -
13 -0.46 0.035 -0.56 0.23 0.00035 -0.45 1.2 0.23 0.053 -0.078 0.026 9.2e+03 6.6 0.0049 0.42 +
14 -0.46 0.035 -0.56 0.23 0.00035 -0.45 1.2 0.23 0.053 -0.078 0.026 9.2e+03 6.6 0.0024 -0.38 -
15 -0.46 0.038 -0.56 0.22 -0.0021 -0.45 1.2 0.22 0.055 -0.08 0.029 9.1e+03 4.8 0.0024 0.5 +
16 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.024 1.2 ++
17 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.012 -1.4 -
18 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.0061 -2.2 -
19 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.0031 -2.9 -
20 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.0015 -2.7 -
21 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.00076 -1.3 -
22 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.00038 0.014 -
23 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.0038 1 ++
24 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.0019 -2.2 -
25 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.00095 -3 -
26 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.00048 -3.6 -
27 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.00024 -1.6 -
28 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.00012 -0.3 -
29 -0.46 0.039 -0.55 0.22 -0.0012 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 0.23 0.00012 0.78 +
30 -0.46 0.039 -0.55 0.22 -0.0012 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 0.12 0.0012 1 ++
31 -0.46 0.039 -0.55 0.22 -0.0012 -0.45 1.2 0.22 0.056 -0.082 0.029 9.1e+03 0.28 0.012 1 ++
32 -0.45 0.042 -0.55 0.21 -0.0012 -0.45 1.2 0.21 0.057 -0.084 0.031 9e+03 0.11 0.12 1 ++
33 -0.42 0.075 -0.51 0.16 -0.00094 -0.44 1.1 0.088 0.062 -0.11 0.043 8.9e+03 0.045 1.2 0.99 ++
34 -0.36 1.3 -0.84 -0.11 0.00017 -1 1.8 -0.82 -0.61 -0.67 -0.46 8.7e+03 8.7 1.2 0.25 +
35 -0.36 1.3 -0.84 -0.11 0.00017 -1 1.8 -0.82 -0.61 -0.67 -0.46 8.7e+03 8.7 0.6 -1.1 -
36 -0.38 0.82 -1.4 0.0021 -0.00028 -0.83 1.9 -0.93 -0.61 -0.69 -0.5 8.5e+03 2.2 0.6 0.35 +
37 -0.38 0.82 -1.4 0.0021 -0.00028 -0.83 1.9 -0.93 -0.61 -0.69 -0.5 8.5e+03 2.2 0.3 -4.6 -
38 -0.38 0.82 -1.4 0.0021 -0.00028 -0.83 1.9 -0.93 -0.61 -0.69 -0.5 8.5e+03 2.2 0.15 -1.6 -
39 -0.39 0.84 -1.5 -0.15 0.00035 -0.91 1.9 -0.85 -0.59 -0.7 -0.49 8.3e+03 24 0.15 0.5 +
40 -0.24 0.86 -1.5 -0.092 0.00016 -0.99 1.8 -0.81 -0.49 -0.72 -0.41 8.2e+03 10 1.5 0.94 ++
41 -0.24 0.86 -1.5 -0.092 0.00016 -0.99 1.8 -0.81 -0.49 -0.72 -0.41 8.2e+03 10 0.42 -0.32 -
42 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.42 0.76 +
43 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.21 -0.68 -
44 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.11 -0.41 -
45 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.053 -0.27 -
46 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.026 -0.3 -
47 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.013 -0.29 -
48 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.0066 -0.41 -
49 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.0033 -0.4 -
50 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.0016 -0.3 -
51 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.00082 -0.26 -
52 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.00041 -0.24 -
53 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.00021 -0.23 -
54 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.0001 -0.23 -
55 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 5.1e-05 -0.11 -
56 -0.19 0.79 -1.7 -0.091 0.00013 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 5.6 5.1e-05 0.67 +
57 -0.19 0.79 -1.7 -0.091 0.00013 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 0.81 0.00051 0.9 ++
58 -0.19 0.79 -1.7 -0.09 0.00012 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 0.014 0.0051 1 ++
59 -0.19 0.79 -1.7 -0.087 0.00011 -1.1 1.4 -0.77 -0.34 -0.87 -0.4 8.2e+03 0.1 0.051 1 ++
60 -0.24 0.8 -1.8 -0.1 0.00018 -1.1 1.4 -0.77 -0.34 -0.89 -0.41 8.2e+03 2.9 0.51 0.95 ++
61 -0.42 1.2 -2.2 -0.11 0.00018 -1.2 1 -0.8 -0.22 -1.1 -0.37 8.2e+03 27 0.51 0.47 +
62 -0.55 1.3 -2.3 -0.11 0.00022 -1.1 1 -0.76 -0.19 -1.1 -0.34 8.2e+03 7 5.1 0.9 ++
63 -0.59 1.3 -2.2 -0.11 0.00019 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 7.8 5.1 0.43 +
64 -0.59 1.3 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 0.67 51 1 ++
65 -0.6 1.3 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 0.013 5.1e+02 1 ++
66 -0.59 1.3 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 1e-05 5.1e+03 1 ++
67 -0.59 1.3 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 5.3e-07 5.1e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 15/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000023
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.54 0.3 -1 -0.54 1.9 0.15 -0.31 -0.00024 -0.62 9.1e+03 0.19 1 0.71 +
1 -0.54 0.3 -1 -0.54 1.9 0.15 -0.31 -0.00024 -0.62 9.1e+03 0.19 0.5 -0.16 -
2 -0.13 0.74 -0.72 -0.6 2.4 -0.3 -0.49 -0.26 -0.46 8.6e+03 0.13 0.5 0.47 +
3 -0.57 0.42 -0.64 -0.41 2.9 -0.29 -0.019 -0.22 -0.45 8.4e+03 0.039 0.5 0.61 +
4 -0.53 0.87 -0.88 -0.45 2.4 -0.31 0.066 -0.18 -0.49 8.3e+03 0.0078 5 1.1 ++
5 -0.53 0.87 -0.88 -0.45 2.4 -0.31 0.066 -0.18 -0.49 8.3e+03 0.0078 0.72 -1.7 -
6 -0.65 0.85 -1 -0.64 1.7 -0.37 -0.29 -0.25 -0.64 8.3e+03 0.0094 7.2 0.95 ++
7 -0.61 0.99 -1.1 -0.73 1.6 -0.3 -0.47 -0.29 -0.65 8.2e+03 0.0016 72 1.1 ++
8 -0.63 1 -1.1 -0.77 1.5 -0.29 -0.56 -0.3 -0.66 8.2e+03 0.00032 7.2e+02 1 ++
9 -0.63 1 -1.1 -0.77 1.5 -0.29 -0.56 -0.3 -0.66 8.2e+03 1.3e-06 7.2e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 16/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000024
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.64 0.089 -0.0056 -1 1.6 -0.96 1.8 0.16 -0.14 -0.023 8.9e+03 0.06 1 0.68 +
1 -0.44 0.92 0.24 -1.3 0.74 -0.41 2.8 0.067 0.016 -0.3 8.8e+03 0.13 1 0.2 +
2 -0.39 0.037 0.31 -0.53 0.59 -0.27 3.8 -0.038 0.081 -0.37 8.7e+03 0.11 1 0.13 +
3 -0.39 0.037 0.31 -0.53 0.59 -0.27 3.8 -0.038 0.081 -0.37 8.7e+03 0.11 0.5 0.0034 -
4 -0.38 0.4 0.034 -0.8 0.41 -0.43 4.3 -0.11 0.11 -0.2 8.6e+03 0.073 0.5 0.62 +
5 -0.38 0.27 0.18 -0.83 0.56 -0.42 3.8 -0.00083 -0.055 -0.38 8.5e+03 0.016 5 1.1 ++
6 -0.38 0.27 0.18 -0.83 0.56 -0.42 3.8 -0.00083 -0.055 -0.38 8.5e+03 0.016 1.4 -2.5 -
7 -0.45 0.53 -0.029 -1.2 0.32 -0.53 2.4 0.035 0.12 -0.3 8.4e+03 0.023 1.4 0.88 +
8 -0.52 0.49 0.3 -1.3 0.47 -0.61 2 0.13 -0.016 -0.38 8.4e+03 0.0066 14 1.1 ++
9 -0.58 0.53 0.36 -1.3 0.47 -0.62 2 0.14 -0.016 -0.44 8.4e+03 0.00049 1.4e+02 1.1 ++
10 -0.59 0.53 0.37 -1.3 0.47 -0.62 1.9 0.14 -0.017 -0.44 8.4e+03 9.1e-06 1.4e+03 1 ++
11 -0.59 0.53 0.37 -1.3 0.47 -0.62 1.9 0.14 -0.017 -0.44 8.4e+03 3.5e-10 1.4e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 17/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000025
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost_train mu_public b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 0 0 0 1 0 1 0 0 0 0 0 0 0 1.1e+04 0.22 0.5 0.034 -
1 -0.5 -0.39 -0.049 1 -0.46 1.4 -0.19 -0.039 0.36 -0.06 -0.14 -0.026 -0.11 9.4e+03 0.15 0.5 0.58 +
2 -0.38 -0.43 -0.075 1.1 -0.44 1.4 -0.37 -0.065 -0.14 -0.19 -0.29 -0.046 -0.25 8.9e+03 0.054 0.5 0.85 +
3 -0.34 -0.82 -0.18 1.1 -0.91 1.6 -0.79 -0.1 -0.64 -0.43 -0.62 -0.072 -0.53 8.6e+03 0.025 5 1 ++
4 -0.34 -0.82 -0.18 1.1 -0.91 1.6 -0.79 -0.1 -0.64 -0.43 -0.62 -0.072 -0.53 8.6e+03 0.025 2.5 1 -
5 -0.34 -0.82 -0.18 1.1 -0.91 1.6 -0.79 -0.1 -0.64 -0.43 -0.62 -0.072 -0.53 8.6e+03 0.025 1.2 -12 -
6 -0.34 -0.82 -0.18 1.1 -0.91 1.6 -0.79 -0.1 -0.64 -0.43 -0.62 -0.072 -0.53 8.6e+03 0.025 0.62 -0.57 -
7 0.25 -1 -0.31 0.68 -1.5 1.7 -1.1 -0.13 -0.87 -0.41 -0.92 -0.067 -0.57 8.4e+03 0.051 0.62 0.86 +
8 0.41 -1.5 -0.51 0.21 -1.6 1.6 -1.3 -0.59 -0.82 -0.17 -1.1 -0.25 -0.79 8.4e+03 0.016 6.2 0.99 ++
9 0.38 -1.8 -0.6 0.27 -1.7 1 -1.5 -0.54 -0.77 -0.11 -1.3 -0.25 -0.66 8.4e+03 0.031 6.2 0.12 +
10 0.42 -2.2 -0.72 0.16 -1.8 1 -1.6 -0.72 -0.76 0.1 -1.4 -0.29 -0.8 8.3e+03 0.0052 62 1.1 ++
11 0.4 -2.2 -0.72 0.16 -1.9 1 -1.6 -0.72 -0.75 0.11 -1.4 -0.29 -0.79 8.3e+03 0.0021 6.2e+02 1 ++
12 0.44 -2.3 -0.75 0.1 -1.9 1 -1.6 -0.73 -0.76 0.13 -1.4 -0.29 -0.82 8.3e+03 0.00013 6.2e+03 1 ++
13 0.44 -2.3 -0.75 0.1 -1.9 1 -1.6 -0.73 -0.76 0.13 -1.4 -0.29 -0.82 8.3e+03 1.7e-07 6.2e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 18/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000026
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car b_time_swissmet Function Relgrad Radius Rho
0 -0.95 0.41 -0.8 1.7 -1 1.8 -0.012 -0.34 -0.58 -0.63 8.8e+03 0.077 1 0.69 +
1 -0.95 0.41 -0.8 1.7 -1 1.8 -0.012 -0.34 -0.58 -0.63 8.8e+03 0.077 0.5 0.085 -
2 -0.65 0.69 -0.77 1.3 -0.5 1.9 -0.28 -0.39 -0.46 -0.79 8.3e+03 0.025 5 0.91 ++
3 -0.11 0.93 -1.8 -0.18 -0.57 2.1 0.19 -0.23 -1.3 -1.9 8.3e+03 0.078 5 0.18 +
4 -0.15 0.97 -2.1 -0.17 -0.58 2 0.095 -0.25 -1.3 -1.3 8.1e+03 0.0062 50 0.95 ++
5 -0.2 1 -2 0.19 -0.62 1.8 0.13 -0.35 -1.3 -1.6 8.1e+03 0.0024 5e+02 0.92 ++
6 -0.23 1 -2 0.16 -0.62 1.8 0.12 -0.35 -1.3 -1.6 8.1e+03 7.1e-05 5e+03 1 ++
7 -0.23 1 -2 0.16 -0.62 1.8 0.12 -0.35 -1.3 -1.6 8.1e+03 8.5e-08 5e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 19/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000027
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.66 0.49 0.1 -0.0046 -0.96 0.06 -1 1.8 0.22 -0.33 -0.11 -0.024 8.5e+03 0.054 10 0.9 ++
1 -0.71 0.74 0.29 0.2 -0.9 0.098 -0.37 2.1 0.0043 -0.54 -0.041 -0.46 8.3e+03 0.017 10 0.77 +
2 -0.93 0.94 0.38 0.32 -1.1 -0.029 -0.57 1.4 0.049 -0.72 -0.033 -0.45 8.3e+03 0.014 10 0.72 +
3 -1 1 0.39 0.33 -1.1 -0.033 -0.62 1.5 0.035 -0.73 -0.02 -0.38 8.2e+03 0.00074 1e+02 1 ++
4 -1 1 0.38 0.32 -1.1 -0.028 -0.61 1.5 0.031 -0.71 -0.022 -0.39 8.2e+03 4.6e-05 1e+03 1 ++
5 -1 1 0.38 0.32 -1.1 -0.028 -0.61 1.5 0.031 -0.71 -0.022 -0.39 8.2e+03 5.9e-08 1e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000028
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_com lambda_travel_t b_cost_train b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho
0 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 10 0.95 ++
1 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 5 -1.3e+05 -
2 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 2.5 -47 -
3 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 1.2 -3.2 -
4 0.1 -1.7 -0.49 0.39 -1.6 -0.89 -0.42 -0.27 8.4e+03 0.025 12 0.95 ++
5 0.28 -1.6 -0.53 0.36 -2 -0.79 -0.13 -0.51 8.4e+03 0.0055 1.2e+02 1.1 ++
6 0.31 -1.6 -0.54 0.36 -2.1 -0.8 -0.14 -0.51 8.4e+03 0.00023 1.2e+03 1 ++
7 0.31 -1.6 -0.54 0.36 -2.1 -0.8 -0.14 -0.51 8.4e+03 3.6e-07 1.2e+03 1 ++
Considering neighbor 1/20 for current solution
Attempt 20/100
Considering neighbor 0/20 for current solution
Attempt 21/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000029
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -1.6 -
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.24 -
2 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 2.5 1.1 ++
3 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 1.2 -5.7 -
4 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.62 -3.1 -
5 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.31 -1.5 -
6 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.16 -0.026 -
7 -0.35 0.027 -0.17 -0.0076 -0.41 -0.26 0.15 -0.003 -0.36 0.19 0.039 -0.056 -0.0074 -0.0042 0.02 9.2e+03 9 0.16 0.51 +
8 -0.35 0.027 -0.17 -0.0076 -0.41 -0.26 0.15 -0.003 -0.36 0.19 0.039 -0.056 -0.0074 -0.0042 0.02 9.2e+03 9 0.078 0.09 -
9 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.078 0.16 +
10 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.039 -4.2 -
11 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.02 -2.8 -
12 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.0098 -2 -
13 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.0049 -1.2 -
14 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.0024 0.099 -
15 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.024 1 ++
16 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.012 -2.9 -
17 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.0061 -2.3 -
18 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.0031 -1.8 -
19 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.0015 -1.1 -
20 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.00076 -0.25 -
21 -0.36 0.051 -0.15 -0.0043 -0.47 -0.27 0.11 -0.001 -0.38 0.11 0.056 -0.077 -0.013 -0.0087 0.04 8.9e+03 2.7 0.00076 0.43 +
22 -0.36 0.051 -0.15 -0.0043 -0.47 -0.27 0.11 -0.001 -0.38 0.11 0.056 -0.077 -0.013 -0.0087 0.04 8.9e+03 2.7 0.00038 -0.84 -
23 -0.36 0.052 -0.15 -0.0039 -0.47 -0.27 0.11 -0.00063 -0.38 0.11 0.056 -0.077 -0.014 -0.0091 0.04 8.9e+03 4.4 0.00038 0.44 +
24 -0.36 0.052 -0.15 -0.0039 -0.47 -0.28 0.11 -0.00086 -0.38 0.11 0.056 -0.077 -0.014 -0.0091 0.04 8.9e+03 2.5 0.00038 0.15 +
25 -0.36 0.052 -0.15 -0.0039 -0.47 -0.28 0.11 -0.00086 -0.38 0.11 0.056 -0.077 -0.014 -0.0091 0.04 8.9e+03 2.5 0.00019 -0.88 -
26 -0.36 0.052 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00067 -0.38 0.11 0.057 -0.078 -0.014 -0.0093 0.04 8.9e+03 3.1 0.00019 0.36 +
27 -0.36 0.052 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00075 -0.38 0.11 0.057 -0.078 -0.014 -0.0093 0.04 8.9e+03 0.6 0.00019 0.83 +
28 -0.36 0.052 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00073 -0.38 0.11 0.057 -0.078 -0.014 -0.0093 0.04 8.9e+03 0.072 0.0019 0.99 ++
29 -0.36 0.053 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00074 -0.38 0.11 0.057 -0.078 -0.014 -0.0094 0.041 8.9e+03 0.089 0.019 1 ++
30 -0.37 0.06 -0.15 -0.0037 -0.48 -0.28 0.12 -0.00076 -0.39 0.089 0.057 -0.085 -0.018 -0.0099 0.042 8.9e+03 0.077 0.19 1 ++
31 -0.4 0.14 -0.1 -0.003 -0.58 -0.32 0.18 -0.001 -0.46 -0.1 0.054 -0.15 -0.056 -0.016 0.051 8.7e+03 0.16 1.9 0.99 ++
32 -0.4 0.14 -0.1 -0.003 -0.58 -0.32 0.18 -0.001 -0.46 -0.1 0.054 -0.15 -0.056 -0.016 0.051 8.7e+03 0.16 0.95 -72 -
33 -0.4 0.14 -0.1 -0.003 -0.58 -0.32 0.18 -0.001 -0.46 -0.1 0.054 -0.15 -0.056 -0.016 0.051 8.7e+03 0.16 0.48 -3.6 -
34 -0.48 0.51 0.14 0.004 -0.78 -0.4 0.07 -0.00056 -0.79 -0.58 -0.17 -0.43 -0.31 -0.045 -0.099 8.4e+03 0.05 4.8 0.98 ++
35 -1.2 1.2 0.4 0.4 -0.95 -0.57 -0.02 -0.00018 -0.97 -0.82 -0.42 -0.78 -0.069 -0.36 -0.31 8.2e+03 0.16 48 1.1 ++
36 -1.1 1.2 0.49 0.5 -1.5 -0.72 -0.13 0.00027 -1 -0.83 -0.28 -0.97 -0.088 -0.46 -0.35 8.2e+03 19 48 0.26 +
37 -0.99 1.2 0.5 0.51 -2 -0.73 -0.094 0.00016 -1.1 -0.87 -0.23 -0.96 -0.11 -0.5 -0.27 8.1e+03 15 48 0.64 +
38 -1 1.2 0.51 0.49 -2 -0.75 -0.11 0.00022 -1.1 -0.86 -0.23 -0.97 -0.11 -0.52 -0.32 8.1e+03 10 48 0.76 +
39 -1.1 1.2 0.51 0.49 -1.8 -0.76 -0.11 0.00019 -1.1 -0.86 -0.24 -0.97 -0.11 -0.53 -0.32 8.1e+03 1.1 4.8e+02 1.1 ++
40 -1.1 1.2 0.51 0.5 -1.8 -0.75 -0.1 0.00019 -1.1 -0.86 -0.24 -0.97 -0.1 -0.53 -0.32 8.1e+03 0.03 4.8e+03 1 ++
41 -1.1 1.2 0.51 0.5 -1.8 -0.75 -0.1 0.00019 -1.1 -0.86 -0.24 -0.97 -0.1 -0.53 -0.32 8.1e+03 3e-05 4.8e+04 1 ++
42 -1.1 1.2 0.51 0.5 -1.8 -0.75 -0.1 0.00019 -1.1 -0.86 -0.24 -0.97 -0.1 -0.53 -0.32 8.1e+03 5.4e-08 4.8e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 22/100
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000030
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 9e+03 0.091 1 0.66 +
1 8.3e+03 0.0081 10 1 ++
2 8.3e+03 0.0081 5 -1e+06 -
3 8.3e+03 0.0081 2.5 -78 -
4 8.3e+03 0.0081 1.2 -2.7 -
5 8.2e+03 0.024 1.2 0.71 +
6 8.1e+03 0.0039 12 0.9 ++
7 8.1e+03 9.1e-05 1.2e+02 1 ++
8 8.1e+03 7.9e-08 1.2e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 7 unknown parameters [max: 50]
*** Estimate b07everything_000031
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_1st b_cost_train b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho
0 -0.65 -0.57 -0.44 -0.88 -0.74 -0.48 -0.54 8.7e+03 0.054 10 1.1 ++
1 -0.29 -0.94 -0.56 -1.5 -0.87 -0.47 -0.37 8.4e+03 0.022 1e+02 1.2 ++
2 -0.17 -0.98 -0.62 -1.8 -0.92 -0.51 -0.36 8.4e+03 0.0041 1e+03 1.1 ++
3 -0.15 -0.98 -0.63 -1.9 -0.92 -0.51 -0.36 8.4e+03 0.00014 1e+04 1 ++
4 -0.15 -0.98 -0.63 -1.9 -0.92 -0.51 -0.36 8.4e+03 1.4e-07 1e+04 1 ++
Considering neighbor 1/20 for current solution
Attempt 23/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000032
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train b_cost b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho
0 -0.92 0.83 0.045 0.013 -0.86 -0.64 -1 -0.25 -0.4 -0.15 -0.059 -0.83 8.5e+03 0.081 10 1.1 ++
1 -1.3 1.3 0.37 0.41 -1.3 -0.72 -1.4 -0.45 -0.85 -0.038 -0.34 -1 8.3e+03 0.023 1e+02 1.1 ++
2 -1.4 1.4 0.53 0.6 -1.4 -0.73 -1.5 -0.46 -1 -0.047 -0.4 -1 8.2e+03 0.0025 1e+03 1.1 ++
3 -1.4 1.4 0.55 0.63 -1.4 -0.73 -1.5 -0.46 -1 -0.047 -0.4 -1 8.2e+03 3.6e-05 1e+04 1 ++
4 -1.4 1.4 0.55 0.63 -1.4 -0.73 -1.5 -0.46 -1 -0.047 -0.4 -1 8.2e+03 1.4e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 24/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000033
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -1.5 -
1 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.055 -
2 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 2.5 1 ++
3 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 1.2 -5.9 -
4 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 0.62 -3.1 -
5 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 0.31 -1.4 -
6 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 0.16 0.00089 -
7 -0.36 -0.41 -0.26 0.15 -0.0031 -0.36 0.21 0.041 0.022 9.2e+03 9.1 0.16 0.53 +
8 -0.36 -0.41 -0.26 0.15 -0.0031 -0.36 0.21 0.041 0.022 9.2e+03 9.1 0.078 0.056 -
9 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.078 0.14 +
10 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.039 -4.2 -
11 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.02 -2.8 -
12 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.0098 -2 -
13 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.0049 -1.2 -
14 -0.38 -0.48 -0.28 0.11 -0.0026 -0.39 0.13 0.059 0.044 9.1e+03 11 0.0049 0.14 +
15 -0.39 -0.48 -0.28 0.11 0.0012 -0.39 0.12 0.06 0.044 9e+03 5.3 0.0049 0.14 +
16 -0.39 -0.48 -0.28 0.11 0.0012 -0.39 0.12 0.06 0.044 9e+03 5.3 0.0024 -0.6 -
17 -0.39 -0.49 -0.28 0.11 -0.0012 -0.39 0.12 0.062 0.047 8.9e+03 4.2 0.0024 0.65 +
18 -0.39 -0.49 -0.28 0.11 -0.00081 -0.39 0.12 0.062 0.047 8.9e+03 2.3 0.024 1.4 ++
19 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.024 0.65 +
20 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.012 -2.2 -
21 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.0061 -2.5 -
22 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.0031 -2.6 -
23 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.0015 -2.7 -
24 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.00076 -0.96 -
25 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.00038 -0.21 -
26 -0.39 -0.5 -0.28 0.12 -0.00094 -0.4 0.092 0.062 0.049 8.9e+03 2.7 0.00038 0.2 +
27 -0.39 -0.5 -0.28 0.12 -0.00094 -0.4 0.092 0.062 0.049 8.9e+03 2.7 0.00019 -0.29 -
28 -0.39 -0.5 -0.29 0.12 -0.00075 -0.4 0.092 0.061 0.049 8.9e+03 0.054 0.00019 0.82 +
29 -0.39 -0.5 -0.29 0.12 -0.00077 -0.4 0.092 0.061 0.049 8.9e+03 0.57 0.0019 1 ++
30 -0.39 -0.5 -0.29 0.12 -0.00076 -0.4 0.09 0.061 0.049 8.9e+03 0.062 0.019 1 ++
31 -0.4 -0.51 -0.29 0.12 -0.00078 -0.41 0.071 0.06 0.049 8.9e+03 0.075 0.19 1 ++
32 -0.44 -0.61 -0.32 0.18 -0.00099 -0.49 -0.12 0.044 0.048 8.8e+03 0.038 1.9 0.99 ++
33 -0.44 -0.61 -0.32 0.18 -0.00099 -0.49 -0.12 0.044 0.048 8.8e+03 0.038 0.95 -48 -
34 -0.44 -0.61 -0.32 0.18 -0.00099 -0.49 -0.12 0.044 0.048 8.8e+03 0.038 0.48 -1.2 -
35 -0.43 -0.81 -0.41 -0.0077 -0.00024 -0.85 -0.6 -0.37 -0.24 8.6e+03 0.63 0.48 0.86 +
36 -0.35 -1.1 -0.61 -0.04 -9.6e-05 -1.3 -0.77 -0.44 -0.26 8.4e+03 0.48 4.8 1.2 ++
37 -0.35 -1.1 -0.61 -0.04 -9.6e-05 -1.3 -0.77 -0.44 -0.26 8.4e+03 0.48 0.5 -4.5 -
38 -0.081 -1.5 -0.82 -0.13 0.00034 -1.8 -0.86 -0.46 -0.33 8.4e+03 6.8 0.5 0.34 +
39 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.5 0.57 +
40 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.25 -1.4 -
41 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.13 -0.49 -
42 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.063 -0.12 -
43 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.032 0.0071 -
44 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.032 0.12 +
45 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.016 -1.4 -
46 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.0079 -1.1 -
47 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.0039 -0.54 -
48 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.002 -0.15 -
49 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.00098 0.03 -
50 0.2 -2 -0.73 -0.12 0.00024 -2 -0.89 -0.38 -0.3 8.3e+03 30 0.00098 0.11 +
51 0.2 -2 -0.73 -0.12 0.00026 -2 -0.89 -0.38 -0.3 8.3e+03 1.8 0.0098 0.94 ++
52 0.2 -2 -0.73 -0.11 0.00022 -2 -0.9 -0.37 -0.3 8.3e+03 3.6 0.098 0.97 ++
53 0.14 -1.9 -0.65 -0.11 0.0002 -2 -0.91 -0.36 -0.34 8.3e+03 0.43 0.98 1 ++
54 0.12 -1.9 -0.68 -0.11 0.0002 -2 -0.91 -0.36 -0.36 8.3e+03 0.03 9.8 1 ++
55 0.12 -1.9 -0.67 -0.11 0.0002 -2 -0.91 -0.36 -0.36 8.3e+03 0.0001 98 1 ++
56 0.12 -1.9 -0.67 -0.11 0.0002 -2 -0.91 -0.36 -0.36 8.3e+03 9.6e-09 98 1 ++
Considering neighbor 0/20 for current solution
Attempt 25/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000034
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car b_time_swissmet b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho
0 -0.76 0.25 -0.62 -0.073 1.4 -0.6 2 0.12 -0.33 -0.44 -0.082 -0.12 -0.63 -0.11 -0.58 9.5e+03 0.22 1 0.57 +
1 -0.76 0.25 -0.62 -0.073 1.4 -0.6 2 0.12 -0.33 -0.44 -0.082 -0.12 -0.63 -0.11 -0.58 9.5e+03 0.22 0.5 -1.3 -
2 -0.26 0.53 -0.5 -0.11 1.2 -0.38 2.3 -0.32 -0.43 -0.41 0.049 -0.45 -0.7 -0.048 -0.52 9e+03 0.22 0.5 0.3 +
3 -0.62 0.51 -0.54 -0.15 1.1 -0.37 2.8 -0.067 -0.39 -0.61 0.11 -0.39 -0.81 -0.021 -0.46 8.4e+03 0.039 0.5 0.81 +
4 -0.34 0.74 -1 -0.27 0.58 -0.43 2.9 -0.1 -0.14 -0.85 0.35 -0.44 -1.2 0.0075 -0.51 8.2e+03 0.022 5 1.1 ++
5 -0.34 0.74 -1 -0.27 0.58 -0.43 2.9 -0.1 -0.14 -0.85 0.35 -0.44 -1.2 0.0075 -0.51 8.2e+03 0.022 0.69 0.058 -
6 -0.086 0.96 -1.7 -0.32 -0.045 -0.53 2.3 0.11 -0.05 -1.3 0.093 -0.51 -1.5 -0.68 -0.55 8.1e+03 0.028 0.69 0.71 +
7 -0.11 0.98 -1.9 -0.55 0.099 -0.62 1.9 0.2 -0.29 -1.3 -0.029 -0.65 -1.5 -0.61 -0.59 8.1e+03 0.0075 6.9 1.1 ++
8 -0.15 1 -2 -0.62 0.096 -0.67 1.8 0.2 -0.38 -1.3 -0.063 -0.67 -1.5 -0.62 -0.6 8.1e+03 0.001 69 1.1 ++
9 -0.15 1 -2 -0.64 0.094 -0.69 1.7 0.2 -0.41 -1.3 -0.074 -0.68 -1.5 -0.63 -0.61 8.1e+03 8.4e-05 6.9e+02 1 ++
10 -0.15 1 -2 -0.64 0.094 -0.69 1.7 0.2 -0.41 -1.3 -0.074 -0.68 -1.5 -0.63 -0.61 8.1e+03 1.3e-07 6.9e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000035
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.53 -
1 1e+04 1.4 0.5 0.28 +
2 1e+04 1.4 0.25 0.28 -
3 1e+04 1.4 0.12 0.28 -
4 1e+04 1.4 0.062 -5.6 -
5 1e+04 1.4 0.031 -0.69 -
6 9.5e+03 1.1 0.031 0.88 +
7 9.5e+03 1.1 0.016 -9.8 -
8 9.3e+03 0.71 0.16 0.94 ++
9 9.1e+03 0.66 1.6 1 ++
10 9.1e+03 0.66 0.78 -3.1 -
11 9.1e+03 0.66 0.39 -0.55 -
12 8.8e+03 8.3 0.39 0.43 +
13 8.8e+03 8.3 0.2 0.43 -
14 8.8e+03 8.3 0.098 0.43 -
15 8.8e+03 8.3 0.049 0.43 -
16 8.8e+03 8.3 0.024 0.43 -
17 8.8e+03 8.3 0.012 0.43 -
18 8.8e+03 8.3 0.0061 -2 -
19 8.8e+03 8.3 0.0031 -1.2 -
20 8.8e+03 8.3 0.0015 -0.12 -
21 8.7e+03 7.2 0.0015 0.87 +
22 8.7e+03 7.2 0.00076 -1.1 -
23 8.7e+03 7.2 0.00038 -1.1 -
24 8.7e+03 7.2 0.00019 -0.44 -
25 8.7e+03 7.5 0.00019 0.28 +
26 8.7e+03 7.5 9.5e-05 -0.12 -
27 8.7e+03 2.5 9.5e-05 0.58 +
28 8.7e+03 0.22 0.00095 0.98 ++
29 8.7e+03 0.29 0.0095 1 ++
30 8.6e+03 0.19 0.095 1 ++
31 8.4e+03 0.089 0.95 0.99 ++
32 8.4e+03 0.089 0.48 -2.7 -
33 8.3e+03 0.1 0.48 0.47 +
34 8.2e+03 0.2 0.48 0.79 +
35 8.1e+03 1.2 0.48 0.29 +
36 8.1e+03 0.034 0.48 0.9 +
37 8.1e+03 0.034 0.24 -5 -
38 8.1e+03 5 0.24 0.23 +
39 8.1e+03 5.7 2.4 0.94 ++
40 8.1e+03 5.7 0.56 -18 -
41 8.1e+03 5.7 0.28 -2.1 -
42 8e+03 9.5 0.28 0.59 +
43 8e+03 1.5 2.8 0.98 ++
44 8e+03 0.2 28 1 ++
45 8e+03 0.0087 2.8e+02 1 ++
46 8e+03 0.00034 2.8e+03 1 ++
47 8e+03 0.00039 2.8e+04 1 ++
48 8e+03 1.1e-05 2.8e+05 1 ++
49 8e+03 0.00055 2.8e+06 1 ++
50 8e+03 6.7e-07 2.8e+06 1 ++
Considering neighbor 1/20 for current solution
*** New pareto solution:
asc:GA;b_cost_gen_altspec:altspec;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power [8037.725562080543, 16]
Attempt 26/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000036
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 0.046 -
1 -0.4 0.013 -0.5 -0.39 1.2 0.3 0.00083 -0.048 -0.024 9.1e+03 0.11 0.5 0.81 +
2 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 5 0.94 ++
3 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 2.5 -1.1e+02 -
4 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 1.2 -15 -
5 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 0.62 -0.65 -
6 -0.35 0.83 -1.2 -0.88 1.4 -0.71 -0.36 -0.55 -0.32 8.3e+03 0.0091 6.2 1 ++
7 -0.53 0.98 -1.2 -1 1.3 -0.76 -0.38 -1 -0.39 8.3e+03 0.0035 62 1.1 ++
8 -0.64 1.1 -1.2 -1 1.2 -0.76 -0.36 -1.1 -0.38 8.3e+03 0.0016 6.2e+02 1.1 ++
9 -0.69 1.1 -1.2 -1 1.1 -0.76 -0.35 -1.1 -0.37 8.3e+03 0.00032 6.2e+03 1.1 ++
10 -0.71 1.2 -1.2 -1 1.1 -0.76 -0.35 -1.1 -0.37 8.3e+03 3.5e-05 6.2e+04 1 ++
11 -0.71 1.2 -1.2 -1 1.1 -0.76 -0.35 -1.1 -0.37 8.3e+03 1.5e-07 6.2e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 27/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000037
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 -0.51 0.37 -0.69 -0.17 -1 2 0.11 -0.29 -0.23 -0.17 -0.42 -0.38 9.3e+03 0.29 1 0.62 +
1 -0.21 0.69 -0.59 -0.41 0 2.4 -0.35 -0.36 -0.38 -0.51 -0.76 -0.31 8.8e+03 0.24 1 0.36 +
2 -0.55 0.49 -0.69 -0.29 -0.43 3.4 -0.45 -0.28 -0.44 -0.34 -0.75 -0.61 8.3e+03 0.057 1 0.72 +
3 -0.61 0.73 -0.72 -0.58 -0.57 2.4 -0.69 0.15 -0.32 -0.65 -0.83 -0.81 8.2e+03 0.0087 10 0.98 ++
4 -0.61 0.91 -0.9 -0.65 -0.67 1.7 -0.58 -0.12 -0.47 -0.72 -0.94 -0.83 8.2e+03 0.012 1e+02 1 ++
5 -0.67 0.99 -0.92 -0.65 -0.67 1.7 -0.55 -0.36 -0.5 -0.71 -0.96 -0.82 8.2e+03 0.0004 1e+03 1 ++
6 -0.69 1 -0.94 -0.66 -0.69 1.7 -0.55 -0.43 -0.52 -0.71 -0.98 -0.82 8.2e+03 0.00024 1e+04 1 ++
7 -0.69 1 -0.94 -0.66 -0.69 1.7 -0.55 -0.43 -0.52 -0.71 -0.98 -0.82 8.2e+03 2.2e-07 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 28/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000038
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.63 0.076 -0.0069 -0.82 -0.53 1.8 -1 1.9 0.22 -0.11 -0.023 9.1e+03 0.11 1 0.55 +
1 -0.63 0.076 -0.0069 -0.82 -0.53 1.8 -1 1.9 0.22 -0.11 -0.023 9.1e+03 0.11 0.5 -0.24 -
2 -0.66 0.29 0.04 -0.42 -0.47 1.5 -0.5 2 0.031 -0.16 -0.093 8.5e+03 0.015 5 0.99 ++
3 -0.66 0.29 0.04 -0.42 -0.47 1.5 -0.5 2 0.031 -0.16 -0.093 8.5e+03 0.015 2.5 -91 -
4 -0.66 0.29 0.04 -0.42 -0.47 1.5 -0.5 2 0.031 -0.16 -0.093 8.5e+03 0.015 1.2 -3.2 -
5 -0.65 0.59 0.23 -1 -0.69 0.25 -0.68 2.1 -0.0085 0.13 -0.32 8.4e+03 0.015 1.2 0.6 +
6 -0.58 0.5 0.31 -1.1 -0.51 0.48 -0.68 1.8 0.18 -0.052 -0.49 8.4e+03 0.0022 12 0.99 ++
7 -0.61 0.51 0.32 -1.1 -0.51 0.49 -0.67 1.9 0.16 -0.048 -0.51 8.4e+03 8.7e-05 1.2e+02 1 ++
8 -0.61 0.51 0.32 -1.1 -0.51 0.49 -0.67 1.9 0.16 -0.048 -0.51 8.4e+03 3.8e-07 1.2e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 29/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000039
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -0.9 -0.02 -0.017 -0.81 -0.4 2 -0.9 -0.71 -0.43 -0.37 -0.35 -0.036 -0.56 -0.46 9.1e+03 0.089 1 0.64 +
1 -1.5 0.91 0.98 -0.59 -0.49 2.1 -0.88 0.021 -1 -0.4 -0.028 -0.69 0.14 -0.45 8.8e+03 0.14 1 0.45 +
2 -1.5 0.91 0.98 -0.59 -0.49 2.1 -0.88 0.021 -1 -0.4 -0.028 -0.69 0.14 -0.45 8.8e+03 0.14 0.5 -1.5 -
3 -1.6 0.84 0.97 -0.54 -0.49 2.2 -0.87 -0.18 -1 -0.27 0.036 -0.69 -0.36 -0.41 8.8e+03 0.058 0.5 0.14 +
4 -1.6 0.84 0.97 -0.54 -0.49 2.2 -0.87 -0.18 -1 -0.27 0.036 -0.69 -0.36 -0.41 8.8e+03 0.058 0.25 -0.02 -
5 -1.6 0.87 0.96 -0.54 -0.5 2 -0.81 -0.13 -1 -0.34 -0.053 -0.68 -0.11 -0.53 8.6e+03 0.0082 2.5 1.1 ++
6 -1.6 0.87 0.96 -0.54 -0.5 2 -0.81 -0.13 -1 -0.34 -0.053 -0.68 -0.11 -0.53 8.6e+03 0.0082 1.2 -0.81 -
7 -1.7 0.9 0.88 -0.9 -0.9 0.71 -0.99 -0.64 -1.2 -0.19 -0.077 -0.63 -0.24 -1.2 8.5e+03 0.039 1.2 0.56 +
8 -0.8 0.83 0.69 -2 -1.1 0.095 -0.86 -1.6 -0.18 0.11 -0.12 -0.61 -0.77 -1 8.4e+03 0.011 12 0.9 ++
9 -0.81 0.85 0.72 -2.1 -1 0.27 -0.88 -1.6 -0.33 0.16 -0.12 -0.62 -0.99 -0.88 8.3e+03 0.00093 1.2e+02 0.95 ++
10 -0.83 0.86 0.73 -2.1 -1 0.25 -0.88 -1.5 -0.36 0.15 -0.12 -0.62 -0.96 -0.9 8.3e+03 3.7e-05 1.2e+03 1 ++
11 -0.83 0.86 0.73 -2.1 -1 0.25 -0.88 -1.5 -0.36 0.15 -0.12 -0.62 -0.96 -0.9 8.3e+03 2.6e-08 1.2e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000040
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 0.94 -0.7 -0.4 -0.63 -0.86 -0.59 -0.49 -0.46 -0.57 -0.53 8.4e+03 0.081 10 1.1 ++
1 -1.1 1.4 -0.96 -0.64 -0.78 -1.1 -0.79 -0.53 -0.87 -0.64 -0.69 8.2e+03 0.018 1e+02 1.1 ++
2 -1 1.5 -1.1 -0.76 -0.8 -1.1 -0.84 -0.55 -1 -0.64 -0.72 8.2e+03 0.002 1e+03 1.1 ++
3 -1 1.5 -1.1 -0.78 -0.8 -1.1 -0.84 -0.55 -1 -0.64 -0.73 8.2e+03 3.7e-05 1e+04 1 ++
4 -1 1.5 -1.1 -0.78 -0.8 -1.1 -0.84 -0.55 -1 -0.64 -0.73 8.2e+03 1.4e-08 1e+04 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000041
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.57 0.079 -0.012 -1 -0.63 1.8 -0.81 -0.38 -0.42 -0.027 9.5e+03 0.1 1 0.55 +
1 -1.6 0.83 0.093 -0.1 -0.43 1.9 -0.43 0.15 -0.068 -0.17 9e+03 0.088 1 0.54 +
2 -1.6 0.89 0.42 -0.45 -0.54 0.88 -0.76 -0.25 0.11 -0.35 8.6e+03 0.037 10 1.1 ++
3 -1.4 0.9 0.93 -0.98 -0.63 0.69 -0.83 0.074 -0.096 -0.6 8.5e+03 0.0092 1e+02 1.2 ++
4 -1.2 0.91 0.86 -1.3 -0.65 0.49 -0.84 0.19 -0.12 -0.65 8.5e+03 0.00086 1e+03 0.95 ++
5 -1.2 0.91 0.86 -1.3 -0.66 0.53 -0.84 0.19 -0.13 -0.65 8.5e+03 7.4e-05 1e+04 0.99 ++
6 -1.2 0.91 0.86 -1.3 -0.66 0.53 -0.84 0.19 -0.13 -0.65 8.5e+03 2.3e-08 1e+04 1 ++
Considering neighbor 2/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000042
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_public asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.77 -0.33 -0.016 -1 -0.11 -0.24 1.6 -0.078 -0.11 -0.0098 9.5e+03 0.12 1 0.43 +
1 -0.4 0.67 0.015 -1.1 -0.14 -1 1.7 -0.2 -0.31 -0.049 8.9e+03 0.1 1 0.49 +
2 -0.57 0.34 0.7 -0.75 -0.21 -0.52 2.1 -0.19 -0.14 -0.58 8.7e+03 0.033 1 0.67 +
3 -0.7 0.46 0.25 -1.1 -0.18 -0.66 1.1 -0.013 -0.1 -0.57 8.6e+03 0.031 1 0.42 +
4 -1 0.74 0.75 -1.2 -0.12 -0.76 1.2 -0.0085 -0.097 -0.55 8.6e+03 0.0015 10 1 ++
5 -1.3 0.9 0.86 -1.3 -0.077 -0.79 1 0.04 -0.077 -0.57 8.6e+03 0.0047 1e+02 0.9 ++
6 -1.4 0.93 0.89 -1.2 -0.08 -0.78 1 0.049 -0.086 -0.56 8.6e+03 0.00032 1e+03 1 ++
7 -1.4 0.94 0.9 -1.3 -0.075 -0.78 1 0.05 -0.079 -0.56 8.6e+03 0.00029 1e+04 1 ++
8 -1.4 0.94 0.9 -1.3 -0.075 -0.78 1 0.05 -0.079 -0.56 8.6e+03 3e-06 1e+04 1 ++
Considering neighbor 3/20 for current solution
Attempt 30/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000043
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 -0.53 0.17 -1 1.4 -0.36 -0.33 -0.11 -0.24 -0.2 8.8e+03 0.049 10 0.96 ++
1 -0.33 1.4 -2.2 -0.041 -0.89 -0.76 -0.14 -0.59 -0.18 8.3e+03 0.022 10 0.74 +
2 -0.49 1.4 -1.8 0.2 -1.1 -0.73 0.0038 -1 -0.49 8.2e+03 0.0039 1e+02 1.1 ++
3 -0.54 1.3 -1.7 0.37 -1.1 -0.75 -0.073 -1.1 -0.46 8.2e+03 0.0016 1e+03 1.1 ++
4 -0.56 1.3 -1.7 0.39 -1.1 -0.75 -0.083 -1.1 -0.46 8.2e+03 3.1e-05 1e+04 1 ++
5 -0.56 1.3 -1.7 0.39 -1.1 -0.75 -0.083 -1.1 -0.46 8.2e+03 2.7e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 31/100
Considering neighbor 0/20 for current solution
Attempt 32/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000044
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 -0.46 0.21 0.0054 -0.01 -1 -0.097 1.3 -0.35 -0.27 -0.17 -0.25 -0.24 -0.021 -0.26 8.9e+03 0.063 10 0.93 ++
1 -0.46 0.21 0.0054 -0.01 -1 -0.097 1.3 -0.35 -0.27 -0.17 -0.25 -0.24 -0.021 -0.26 8.9e+03 0.063 5 -4.3e+05 -
2 -0.46 0.21 0.0054 -0.01 -1 -0.097 1.3 -0.35 -0.27 -0.17 -0.25 -0.24 -0.021 -0.26 8.9e+03 0.063 2.5 -55 -
3 -0.46 0.21 0.0054 -0.01 -1 -0.097 1.3 -0.35 -0.27 -0.17 -0.25 -0.24 -0.021 -0.26 8.9e+03 0.063 1.2 -1.8 -
4 -0.79 1.3 0.36 0.1 -1.9 -0.58 0.079 -1.1 -0.98 -0.36 -0.8 0.014 -0.15 -0.37 8.3e+03 0.028 1.2 0.8 +
5 -0.85 1.2 0.53 0.51 -1.7 -0.61 0.27 -1.1 -0.71 0.068 -1 -0.094 -0.5 -0.5 8.2e+03 0.0015 12 1 ++
6 -0.9 1.2 0.55 0.51 -1.7 -0.58 0.34 -1.1 -0.74 0.00081 -1 -0.081 -0.51 -0.49 8.2e+03 0.00025 1.2e+02 1 ++
7 -0.9 1.2 0.55 0.51 -1.7 -0.58 0.34 -1.1 -0.74 0.00081 -1 -0.081 -0.51 -0.49 8.2e+03 1.2e-06 1.2e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000045
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2.1 -
1 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.13 -
2 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 2.5 1 ++
3 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 1.2 -5.7 -
4 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.62 -4.2 -
5 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.31 -1.5 -
6 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.16 -0.15 -
7 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.16 0.23 +
8 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.078 -0.79 -
9 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.039 -0.7 -
10 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.02 -0.65 -
11 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.0098 -0.52 -
12 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.0049 -0.087 -
13 -0.36 0.02 -0.41 -0.084 0.12 0.0011 -0.36 0.23 0.033 -0.052 0.013 9.2e+03 5.2 0.0049 0.34 +
14 -0.36 0.02 -0.41 -0.084 0.12 0.0011 -0.36 0.23 0.033 -0.052 0.013 9.2e+03 5.2 0.0024 -0.51 -
15 -0.36 0.022 -0.41 -0.081 0.12 -0.0013 -0.36 0.23 0.036 -0.054 0.016 9.1e+03 4.5 0.0024 0.63 +
16 -0.36 0.023 -0.42 -0.082 0.12 -0.00086 -0.36 0.23 0.036 -0.055 0.016 9.1e+03 2.7 0.024 1.3 ++
17 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.024 0.66 +
18 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.012 -2.7 -
19 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.0061 -2.1 -
20 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.0031 -1.7 -
21 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.0015 -1.1 -
22 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.00076 -0.49 -
23 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.00038 0.068 -
24 -0.37 0.03 -0.44 -0.086 0.14 -0.0009 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 2.6 0.00038 0.62 +
25 -0.37 0.03 -0.44 -0.086 0.14 -0.0009 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 2.6 0.00019 -0.88 -
26 -0.37 0.03 -0.44 -0.086 0.14 -0.0009 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 2.6 9.5e-05 -0.57 -
27 -0.37 0.031 -0.44 -0.086 0.14 -0.00081 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 1.2 9.5e-05 0.64 +
28 -0.37 0.031 -0.44 -0.086 0.14 -0.00083 -0.37 0.21 0.042 -0.063 0.022 9e+03 0.059 0.00095 1 ++
29 -0.37 0.031 -0.44 -0.086 0.14 -0.00083 -0.38 0.2 0.042 -0.064 0.022 9e+03 0.33 0.0095 1 ++
30 -0.38 0.034 -0.45 -0.087 0.14 -0.00085 -0.38 0.19 0.044 -0.067 0.024 9e+03 0.058 0.095 1 ++
31 -0.42 0.065 -0.53 -0.098 0.19 -0.0011 -0.43 0.099 0.057 -0.098 0.038 8.9e+03 0.2 0.95 0.99 ++
32 -0.68 1 -1 -0.23 -0.14 0.00034 -1.2 -0.67 -0.36 -0.61 -0.29 8.5e+03 13 0.95 0.65 +
33 -0.68 1 -1 -0.23 -0.14 0.00034 -1.2 -0.67 -0.36 -0.61 -0.29 8.5e+03 13 0.48 -0.16 -
34 -0.73 1 -1.5 -0.34 -0.025 -0.00013 -1.2 -0.63 -0.4 -0.63 -0.36 8.3e+03 14 0.48 0.46 +
35 -0.73 1 -1.5 -0.34 -0.025 -0.00013 -1.2 -0.63 -0.4 -0.63 -0.36 8.3e+03 14 0.24 -0.39 -
36 -0.7 1.1 -1.7 -0.41 -0.12 0.00022 -1.2 -0.8 -0.3 -0.67 -0.3 8.2e+03 37 0.24 0.44 +
37 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.24 0.62 +
38 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.12 -4.1 -
39 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.06 -4.1 -
40 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.03 -3.8 -
41 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.015 -3.7 -
42 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.0075 -3.6 -
43 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.0037 -3.7 -
44 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.0019 -3.7 -
45 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00093 -3.7 -
46 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00047 -2.6 -
47 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00023 -1.6 -
48 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00012 -0.72 -
49 -0.56 1.2 -2 -0.56 -0.093 9e-05 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 32 0.00012 0.19 +
50 -0.56 1.2 -2 -0.56 -0.093 9e-05 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 32 5.8e-05 -0.26 -
51 -0.56 1.2 -2 -0.56 -0.093 0.00015 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 17 5.8e-05 0.6 +
52 -0.56 1.2 -2 -0.56 -0.093 0.00013 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 12 5.8e-05 0.42 +
53 -0.56 1.2 -2 -0.56 -0.093 0.00014 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 2.5 5.8e-05 0.85 +
54 -0.56 1.2 -2 -0.56 -0.093 0.00014 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 0.033 0.00058 1 ++
55 -0.56 1.2 -2 -0.56 -0.094 0.00014 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 0.041 0.0058 1 ++
56 -0.56 1.2 -2 -0.56 -0.099 0.00016 -1.2 -0.8 -0.3 -0.73 -0.35 8.2e+03 0.64 0.058 0.97 ++
57 -0.6 1.2 -2 -0.62 -0.1 0.00018 -1.2 -0.78 -0.26 -0.75 -0.34 8.1e+03 0.26 0.58 1 ++
58 -0.57 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.35 8.1e+03 1 5.8 1 ++
59 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.36 8.1e+03 0.022 58 1 ++
60 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.36 8.1e+03 3.8e-05 5.8e+02 1 ++
61 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.36 8.1e+03 1.4e-06 5.8e+02 1 ++
Considering neighbor 1/20 for current solution
Attempt 33/100
Considering neighbor 0/20 for current solution
Attempt 34/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000046
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 -0.51 0.26 0.0094 -0.0091 -1 -0.42 -0.4 -0.1 -0.28 -0.2 -0.024 -0.2 8.7e+03 0.061 10 1.1 ++
1 -1.1 1.3 0.35 0.38 -1.2 -0.82 -0.71 -0.31 -0.7 -0.035 -0.31 -0.34 8.3e+03 0.015 1e+02 1.1 ++
2 -1.2 1.2 0.53 0.58 -1.3 -1 -0.75 -0.31 -1 -0.042 -0.42 -0.35 8.2e+03 0.0015 1e+03 1.1 ++
3 -1.2 1.1 0.56 0.61 -1.3 -1 -0.76 -0.31 -1.1 -0.043 -0.43 -0.35 8.2e+03 3.4e-05 1e+04 1 ++
4 -1.2 1.1 0.56 0.61 -1.3 -1 -0.76 -0.31 -1.1 -0.043 -0.43 -0.35 8.2e+03 2.9e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 35/100
Biogeme parameters read from biogeme.toml.
Model with 18 unknown parameters [max: 50]
*** Estimate b07everything_000047
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.26 -
1 9.6e+03 1 0.5 0.65 +
2 9.6e+03 1 0.25 0.65 -
3 9.6e+03 1 0.12 0.65 -
4 9.6e+03 1 0.062 -13 -
5 9.6e+03 1 0.031 -19 -
6 9.6e+03 1 0.016 -2.5 -
7 9.4e+03 0.44 0.16 0.97 ++
8 9.4e+03 0.44 0.078 -13 -
9 9.4e+03 0.44 0.039 -11 -
10 9.4e+03 0.44 0.02 -10 -
11 9.4e+03 0.44 0.0098 -11 -
12 9.4e+03 0.44 0.0049 -4.7 -
13 9.4e+03 0.44 0.0024 0.036 -
14 9.4e+03 0.24 0.024 0.96 ++
15 9.4e+03 0.24 0.012 -0.14 -
16 9.4e+03 0.24 0.0061 -0.009 -
17 9.4e+03 0.24 0.0031 -0.096 -
18 9.4e+03 0.24 0.0015 -0.39 -
19 9.4e+03 0.84 0.0015 0.75 +
20 9.4e+03 0.27 0.015 1.1 ++
21 9.3e+03 0.073 0.15 1 ++
22 9.2e+03 2.4 0.15 0.85 +
23 9.2e+03 2.4 0.076 -7.1 -
24 9.2e+03 2.4 0.038 -7.4 -
25 9.2e+03 2.4 0.019 -7.8 -
26 9.2e+03 2.4 0.0095 -8.1 -
27 9.2e+03 2.4 0.0048 -5.1 -
28 9.2e+03 2.4 0.0024 -2.8 -
29 9.2e+03 2.4 0.0012 -1 -
30 9.2e+03 2.4 0.0006 0.053 -
31 9.2e+03 0.77 0.0006 0.74 +
32 9.2e+03 0.19 0.006 0.96 ++
33 9.1e+03 0.076 0.06 1 ++
34 9.1e+03 0.11 0.6 1 ++
35 8.6e+03 4.8 0.6 0.71 +
36 8.6e+03 4.8 0.3 -1.6 -
37 8.5e+03 4.8 0.3 0.22 +
38 8.5e+03 4.8 0.15 0.22 -
39 8.5e+03 4.8 0.075 -2.4 -
40 8.5e+03 4.8 0.037 -2.1 -
41 8.5e+03 4.8 0.019 -1.8 -
42 8.5e+03 4.8 0.0093 -1.6 -
43 8.5e+03 4.8 0.0047 -1.4 -
44 8.5e+03 4.8 0.0023 -1.1 -
45 8.5e+03 4.8 0.0012 -0.7 -
46 8.5e+03 8.3 0.0012 0.13 +
47 8.5e+03 8.3 0.00058 0.0093 -
48 8.5e+03 4.8 0.00058 0.53 +
49 8.5e+03 4.8 0.00029 -0.74 -
50 8.5e+03 4.8 0.00015 0.068 -
51 8.5e+03 3 0.0015 0.95 ++
52 8.5e+03 2.1 0.015 0.91 ++
53 8.5e+03 0.11 0.15 1 ++
54 8.3e+03 0.052 1.5 1.1 ++
55 8.3e+03 0.052 0.73 -17 -
56 8.2e+03 0.69 0.73 0.63 +
57 8.1e+03 0.97 7.3 0.95 ++
58 8.1e+03 0.015 73 1.1 ++
59 8.1e+03 0.0035 7.3e+02 1 ++
60 8.1e+03 0.0035 3.6e+02 1 -
61 8.1e+03 0.0035 1.8e+02 1 -
62 8.1e+03 0.0035 91 1 -
63 8.1e+03 0.0035 45 1 -
64 8.1e+03 0.0035 23 1 -
65 8.1e+03 0.0035 11 1 -
66 8.1e+03 0.0035 5.7 1 -
67 8.1e+03 0.0035 2.8 -9.3e+02 -
68 8.1e+03 0.0035 1.4 -3.1e+02 -
69 8.1e+03 0.0035 0.71 -49 -
70 8.1e+03 0.0035 0.36 -3.5 -
71 8.1e+03 0.46 0.36 0.54 +
72 8.1e+03 0.46 3.6 1.1 ++
73 8.1e+03 0.46 0.72 -22 -
74 8.1e+03 0.46 0.36 -2.8 -
75 8.1e+03 1.7 0.36 0.61 +
76 8.1e+03 0.89 3.6 1 ++
77 8.1e+03 0.17 36 1 ++
78 8.1e+03 0.0039 3.6e+02 1 ++
79 8.1e+03 0.00063 3.6e+03 1 ++
80 8.1e+03 1.8e-05 3.6e+04 1 ++
81 8.1e+03 4.1e-07 3.6e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 36/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000048
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 0 -
1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.25 -0.22 -
2 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 2.5 1 ++
3 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 1.2 -5.8 -
4 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.62 -3.2 -
5 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.31 -1.4 -
6 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.16 -0.4 -
7 -0.35 -0.17 -0.0076 -0.41 -0.26 0.15 -0.0031 -0.36 1.1 0.19 0.037 -0.0084 -0.0042 0.019 9.2e+03 9 0.16 0.47 +
8 -0.35 -0.17 -0.0076 -0.41 -0.26 0.15 -0.0031 -0.36 1.1 0.19 0.037 -0.0084 -0.0042 0.019 9.2e+03 9 0.078 0.08 -
9 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.078 0.15 +
10 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.039 -4.5 -
11 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.02 -2.9 -
12 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.0098 -2.1 -
13 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.0049 -1.2 -
14 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.0024 0.052 -
15 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.024 1 ++
16 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.012 -3.2 -
17 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.0061 -2.5 -
18 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.0031 -1.9 -
19 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.0015 -1.2 -
20 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.00076 -0.34 -
21 -0.34 -0.14 -0.0062 -0.46 -0.27 0.1 -0.001 -0.36 1.1 0.11 0.042 -0.018 -0.0066 0.028 9e+03 2.8 0.00076 0.34 +
22 -0.34 -0.14 -0.0062 -0.46 -0.27 0.1 -0.001 -0.36 1.1 0.11 0.042 -0.018 -0.0066 0.028 9e+03 2.8 0.00038 -0.79 -
23 -0.34 -0.14 -0.0059 -0.46 -0.27 0.1 -0.00063 -0.37 1.1 0.11 0.041 -0.019 -0.007 0.028 8.9e+03 3.1 0.00038 0.71 +
24 -0.34 -0.14 -0.0059 -0.46 -0.27 0.1 -0.00072 -0.37 1.1 0.11 0.041 -0.019 -0.007 0.028 8.9e+03 0.72 0.00038 0.82 +
25 -0.34 -0.14 -0.0059 -0.46 -0.27 0.1 -0.0007 -0.37 1.1 0.11 0.041 -0.019 -0.0071 0.028 8.9e+03 0.11 0.0038 0.98 ++
26 -0.34 -0.14 -0.0058 -0.46 -0.27 0.1 -0.00071 -0.37 1.1 0.11 0.041 -0.02 -0.0072 0.028 8.9e+03 0.061 0.038 1 ++
27 -0.34 -0.13 -0.0055 -0.47 -0.27 0.12 -0.00075 -0.38 1.1 0.068 0.038 -0.028 -0.0083 0.027 8.9e+03 0.11 0.38 1 ++
28 -0.35 0.016 -0.0022 -0.64 -0.34 0.21 -0.0011 -0.5 1.1 -0.31 -0.011 -0.13 -0.021 0.0084 8.7e+03 0.3 3.8 0.96 ++
29 -0.35 0.016 -0.0022 -0.64 -0.34 0.21 -0.0011 -0.5 1.1 -0.31 -0.011 -0.13 -0.021 0.0084 8.7e+03 0.3 1.9 0.96 -
30 -0.35 0.016 -0.0022 -0.64 -0.34 0.21 -0.0011 -0.5 1.1 -0.31 -0.011 -0.13 -0.021 0.0084 8.7e+03 0.3 0.95 -50 -
31 -0.35 0.016 -0.0022 -0.64 -0.34 0.21 -0.0011 -0.5 1.1 -0.31 -0.011 -0.13 -0.021 0.0084 8.7e+03 0.3 0.48 -3.3 -
32 -0.47 0.24 0.012 -0.78 -0.41 -0.1 0.00013 -0.98 1.2 -0.43 -0.29 -0.35 -0.057 -0.18 8.5e+03 7.8 0.48 0.61 +
33 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.48 0.67 +
34 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.24 -2.3 -
35 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.12 -0.66 -
36 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.06 -0.16 -
37 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.03 -0.012 -
38 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.015 -0.22 -
39 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.0075 -0.57 -
40 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.0037 -1.2 -
41 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.0019 -1.9 -
42 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.00093 -2.5 -
43 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.00047 -3 -
44 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.00023 -3.3 -
45 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.00012 -2.7 -
46 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 5.8e-05 -0.81 -
47 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00017 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 3.1 5.8e-05 0.63 +
48 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00018 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 0.22 0.00058 1 ++
49 -0.36 0.49 0.051 -1.3 -0.66 -0.022 -0.00018 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 0.13 0.0058 1 ++
50 -0.36 0.49 0.051 -1.3 -0.66 -0.028 -0.00015 -1.1 1.3 -0.78 -0.31 -0.23 -0.094 -0.25 8.3e+03 0.2 0.058 1 ++
51 -0.39 0.47 0.056 -1.3 -0.66 -0.086 9.1e-05 -1.2 1.3 -0.74 -0.32 -0.23 -0.098 -0.25 8.3e+03 3.6 0.058 0.85 +
52 -0.4 0.47 0.066 -1.3 -0.67 -0.091 0.00012 -1.2 1.4 -0.72 -0.33 -0.22 -0.11 -0.27 8.3e+03 0.38 0.58 1 ++
53 -0.35 0.55 0.35 -1.8 -0.68 -0.11 0.00021 -1.7 1 -0.9 -0.32 -0.14 -0.31 -0.34 8.3e+03 3 5.8 0.91 ++
54 -0.42 0.67 0.4 -1.9 -0.67 -0.11 0.00019 -1.8 1 -0.9 -0.29 -0.16 -0.38 -0.33 8.2e+03 2 58 1 ++
55 -0.49 0.74 0.61 -1.9 -0.66 -0.11 0.0002 -1.8 1 -0.9 -0.28 -0.15 -0.6 -0.34 8.2e+03 0.062 5.8e+02 1 ++
56 -0.49 0.74 0.58 -1.9 -0.67 -0.11 0.0002 -1.8 1 -0.9 -0.28 -0.15 -0.64 -0.34 8.2e+03 0.0011 5.8e+03 1 ++
57 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 1 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 0.00091 5.8e+04 1 ++
58 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 1 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 1.5e-06 5.8e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 37/100
Biogeme parameters read from biogeme.toml.
Model with 20 unknown parameters [max: 50]
*** Estimate b07everything_000049
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.53 -
1 1.1e+04 0.4 0.25 0.02 -
2 9.7e+03 1.1 0.25 0.77 +
3 9.7e+03 1.1 0.12 -6.8 -
4 1.8e+04 5.4 1.2 6.9 ++
5 1.8e+04 5.4 0.62 -0.44 -
6 1.8e+04 5.4 0.31 -0.093 -
7 1.2e+04 2.1 3.1 1.5 ++
8 1.2e+04 2.1 1.6 1.5 -
9 1.2e+04 2.1 0.78 1.5 -
10 1.2e+04 2.1 0.39 1.5 -
11 1.2e+04 2.1 0.2 -1.6 -
12 1.2e+04 2.1 0.098 -0.89 -
13 1.1e+04 2.3 0.098 0.49 +
14 9.5e+03 0.18 0.98 1.2 ++
15 9.5e+03 0.18 0.49 1.2 -
16 9.5e+03 0.18 0.24 1.2 -
17 9.5e+03 0.18 0.12 -9.7 -
18 9.5e+03 0.18 0.061 -7.6 -
19 9.5e+03 0.18 0.031 -6.2 -
20 9.5e+03 0.18 0.015 -3.3 -
21 9.5e+03 1.8 0.015 0.51 +
22 9.4e+03 0.11 0.015 0.63 +
23 9.4e+03 0.11 0.0076 -3.7 -
24 9.4e+03 0.11 0.0038 0.051 -
25 9.4e+03 0.1 0.038 0.97 ++
26 9.3e+03 0.12 0.38 1 ++
27 9.3e+03 0.12 0.19 1 -
28 9.3e+03 0.12 0.095 -11 -
29 9.3e+03 0.12 0.048 -8.9 -
30 9.3e+03 0.12 0.024 -8.4 -
31 9.3e+03 0.12 0.012 -9.5 -
32 9.3e+03 0.12 0.006 -3 -
33 9.3e+03 0.12 0.003 0.098 -
34 9.3e+03 0.072 0.03 0.97 ++
35 9.3e+03 0.072 0.015 -2.1 -
36 9.3e+03 0.072 0.0075 -0.52 -
37 9.3e+03 0.072 0.0037 0.00069 -
38 9.3e+03 1.1 0.0037 0.42 +
39 9.3e+03 0.067 0.0037 0.87 +
40 9.3e+03 0.067 0.0019 -0.23 -
41 9.3e+03 0.81 0.0019 0.38 +
42 9.3e+03 0.064 0.019 0.94 ++
43 9.2e+03 0.32 0.19 1.3 ++
44 9.2e+03 0.32 0.093 -9.9 -
45 9.2e+03 0.32 0.047 -10 -
46 9.2e+03 0.32 0.023 -11 -
47 9.2e+03 0.32 0.012 -14 -
48 9.2e+03 0.32 0.0058 -3 -
49 9.2e+03 0.32 0.0029 -0.17 -
50 9.2e+03 0.2 0.029 0.98 ++
51 9.1e+03 1.6 0.029 0.81 +
52 9.1e+03 0.75 0.029 0.63 +
53 9.1e+03 0.75 0.015 -9.8 -
54 9.1e+03 0.75 0.0073 -4.3 -
55 9.1e+03 0.75 0.0036 -2.2 -
56 9.1e+03 0.75 0.0018 -0.13 -
57 9.1e+03 0.39 0.018 0.97 ++
58 9e+03 0.51 0.18 0.99 ++
59 8.7e+03 0.88 1.8 0.95 ++
60 8.7e+03 0.88 0.91 -8.2 -
61 8.5e+03 0.42 0.91 0.41 +
62 8.5e+03 0.42 0.45 -1.2 -
63 8.3e+03 1.6 0.45 0.62 +
64 8.3e+03 1.6 0.23 -0.31 -
65 8.2e+03 2.1 2.3 0.97 ++
66 8.2e+03 2.1 1.1 -2.6e+02 -
67 8.2e+03 2.1 0.57 -60 -
68 8.2e+03 2.1 0.28 -11 -
69 8.2e+03 2.1 0.14 -3 -
70 8.2e+03 2.1 0.071 -1.4 -
71 8.2e+03 2.1 0.036 -1.4 -
72 8.2e+03 2.1 0.018 -1.4 -
73 8.2e+03 2.1 0.0089 -1.4 -
74 8.2e+03 2.1 0.0044 -1.6 -
75 8.2e+03 2.1 0.0022 -2 -
76 8.2e+03 2.1 0.0011 -2.4 -
77 8.2e+03 2.1 0.00056 -2.6 -
78 8.2e+03 2.1 0.00028 -1.5 -
79 8.2e+03 2.1 0.00014 -0.084 -
80 8.2e+03 0.34 0.00014 0.83 +
81 8.2e+03 0.034 0.0014 0.99 ++
82 8.2e+03 0.076 0.014 1 ++
83 8.2e+03 0.0061 0.14 1 ++
84 8.2e+03 2.2 0.14 0.75 +
85 8.2e+03 6.3 0.14 0.67 +
86 8.2e+03 6.3 0.069 -0.71 -
87 8.2e+03 6.3 0.035 -0.56 -
88 8.2e+03 6.3 0.017 -0.57 -
89 8.2e+03 6.3 0.0087 -0.66 -
90 8.2e+03 6.3 0.0043 -0.73 -
91 8.2e+03 6.3 0.0022 -0.75 -
92 8.2e+03 6.3 0.0011 -0.77 -
93 8.2e+03 6.3 0.00054 -0.78 -
94 8.2e+03 6.3 0.00027 -0.8 -
95 8.2e+03 6.3 0.00014 0.025 -
96 8.2e+03 1.5 0.00014 0.6 +
97 8.2e+03 0.39 0.00014 0.84 +
98 8.2e+03 0.0087 0.0014 1 ++
99 8.2e+03 0.011 0.014 1 ++
100 8.2e+03 0.0063 0.14 1 ++
101 8.2e+03 0.16 1.4 1 ++
102 8.2e+03 0.16 0.46 -5.9 -
103 8.2e+03 6.3 0.46 0.4 +
104 8.1e+03 2.1 4.6 1 ++
105 8.1e+03 0.89 4.6 0.9 +
106 8.1e+03 3.5 46 1 ++
107 8.1e+03 0.28 4.6e+02 1 ++
108 8.1e+03 0.0059 4.6e+03 1 ++
109 8.1e+03 2.4e-05 4.6e+04 1 ++
110 8.1e+03 0.00081 4.6e+05 1 ++
111 8.1e+03 4.1e-08 4.6e+05 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000050
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 1 0.62 +
1 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 0.5 -0.081 -
2 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 5 0.9 ++
3 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 2.5 -1e+02 -
4 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 1.2 -5.7 -
5 -0.39 1.1 -1.2 -0.68 0.18 -0.6 2.1 0.016 -0.38 -0.66 -0.79 -1.3 -0.69 8.1e+03 0.018 1.2 0.71 +
6 -0.35 1.2 -1.7 -0.75 0.2 -0.73 1.4 0.14 -0.59 -0.95 -0.82 -1.5 -0.26 8.1e+03 0.011 1.2 0.73 +
7 -0.3 1.1 -1.8 -0.72 0.16 -0.72 1.6 0.14 -0.43 -0.95 -0.81 -1.5 -0.25 8.1e+03 0.0012 12 1.1 ++
8 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.39 -0.93 -0.79 -1.5 -0.25 8.1e+03 0.00084 1.2e+02 1.1 ++
9 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 2.3e-05 1.2e+03 1 ++
10 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 3.1e-08 1.2e+03 1 ++
Considering neighbor 1/20 for current solution
*** New pareto solution:
asc:GA;b_cost_gen_altspec:generic;b_time:FIRST;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:boxcox [8069.9882457623635, 13]
Attempt 38/100
Biogeme parameters read from biogeme.toml.
Model with 17 unknown parameters [max: 50]
*** Estimate b07everything_000051
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 9.8e+03 0.16 1 0.25 +
1 9.8e+03 0.16 0.5 0.0022 -
2 8.6e+03 0.074 0.5 0.77 +
3 8.3e+03 0.011 0.5 0.9 +
4 8.2e+03 0.017 5 1 ++
5 8.1e+03 0.013 50 1.2 ++
6 8.1e+03 0.0081 5e+02 1.3 ++
7 8.1e+03 0.0022 5e+03 1 ++
8 8.1e+03 0.00027 5e+04 1 ++
9 8.1e+03 4e-07 5e+04 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000052
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost_train b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car b_cost_car Function Relgrad Radius Rho
0 -0.97 0.37 -0.045 -0.022 -0.77 1.6 -0.6 -1 -0.67 -0.27 -0.47 -0.38 -0.042 -0.76 -0.53 8.7e+03 0.04 10 0.9 ++
1 -0.97 0.37 -0.045 -0.022 -0.77 1.6 -0.6 -1 -0.67 -0.27 -0.47 -0.38 -0.042 -0.76 -0.53 8.7e+03 0.04 1.6 -5.4 -
2 -1.1 1.8 0.53 0.34 -1.8 -0.0076 -0.9 -2.4 -0.94 -0.25 -1.1 -0.041 -0.28 -2.3 -0.093 8.5e+03 0.09 1.6 0.37 +
3 -0.66 0.99 0.52 0.62 -2.4 -0.15 -0.99 -1.3 -0.63 0.25 -0.95 -0.088 -0.43 -1.3 -0.84 8.2e+03 0.022 1.6 0.79 +
4 -0.77 1.1 0.53 0.52 -2.2 0.28 -1 -1.7 -0.72 0.15 -0.97 -0.084 -0.46 -1.5 -0.71 8.2e+03 0.0055 16 0.99 ++
5 -0.77 1.2 0.53 0.51 -2.3 0.2 -1 -1.7 -0.73 0.17 -0.96 -0.086 -0.46 -1.5 -0.73 8.2e+03 0.00037 1.6e+02 0.98 ++
6 -0.77 1.2 0.53 0.51 -2.3 0.2 -1 -1.7 -0.73 0.17 -0.96 -0.086 -0.46 -1.5 -0.73 8.2e+03 1.7e-06 1.6e+02 1 ++
Considering neighbor 1/20 for current solution
Attempt 39/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000053
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.79 0.43 -0.87 0.091 -1 1.6 0.37 -0.31 8.8e+03 0.12 1 0.79 +
1 -0.79 0.43 -0.87 0.091 -1 1.6 0.37 -0.31 8.8e+03 0.12 0.5 -0.11 -
2 -0.63 0.75 -1.1 0.068 -0.5 1.8 -0.06 -0.42 8.3e+03 0.021 0.5 0.89 +
3 -0.7 1 -1 -0.0077 -0.59 1.6 0.019 -0.57 8.3e+03 0.0019 5 1 ++
4 -0.74 1.1 -1.1 -0.016 -0.61 1.5 0.019 -0.69 8.3e+03 0.00013 50 1.1 ++
5 -0.74 1.1 -1.1 -0.019 -0.61 1.5 0.02 -0.72 8.3e+03 8.1e-06 5e+02 1 ++
6 -0.74 1.1 -1.1 -0.019 -0.61 1.5 0.02 -0.72 8.3e+03 9.8e-10 5e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 40/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000054
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.7 0.27 -1 0.0041 1.6 -0.57 -0.27 -0.24 8.8e+03 0.045 1 0.84 +
1 -1.1 1.3 -1.3 0.036 0.85 -0.79 -0.033 -0.63 8.3e+03 0.013 10 1.1 ++
2 -0.66 1.7 -2 -0.87 -0.062 -0.71 0.32 -1.1 8.3e+03 0.032 10 0.11 +
3 -0.85 1.7 -1.7 -0.61 0.19 -0.71 0.21 -1.2 8.2e+03 0.0037 1e+02 1.1 ++
4 -0.88 1.7 -1.6 -0.59 0.32 -0.71 0.18 -1.2 8.2e+03 0.00099 1e+03 1.1 ++
5 -0.89 1.7 -1.6 -0.58 0.34 -0.71 0.18 -1.2 8.2e+03 1.4e-05 1e+04 1 ++
6 -0.89 1.7 -1.6 -0.58 0.34 -0.71 0.18 -1.2 8.2e+03 4.6e-09 1e+04 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000055
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 10 0.96 ++
1 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 5 -7.9e+05 -
2 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 2.5 -42 -
3 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 1.2 -0.38 -
4 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 12 1 ++
5 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 5.6 -4.5e+07 -
6 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 2.8 -4.4e+02 -
7 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 1.4 -12 -
8 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 0.7 -0.046 -
9 -1.1 1.6 -1.3 -0.31 0.51 -0.71 -1.4 0.029 -0.035 -0.74 -1 -0.016 8.2e+03 0.013 7 0.97 ++
10 -0.66 1.6 -2.2 -0.71 0.097 -0.72 -1.6 -0.88 0.13 -0.96 -1.4 -0.29 8.2e+03 0.0093 70 0.98 ++
11 -0.63 1.6 -2.3 -0.86 0.16 -0.73 -1.6 -0.72 0.14 -1 -1.5 -0.27 8.2e+03 0.00023 7e+02 0.99 ++
12 -0.63 1.6 -2.3 -0.86 0.16 -0.73 -1.6 -0.72 0.14 -1 -1.5 -0.27 8.2e+03 2.3e-06 7e+02 1 ++
Considering neighbor 1/20 for current solution
Attempt 41/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000056
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 -0.4 -0.022 -0.8 -0.091 1.2 -0.34 1.7 -0.39 -0.081 -0.32 -0.28 -0.017 -0.41 -0.062 9.8e+03 0.15 1 0.3 +
1 -0.48 0.6 0.0066 -0.66 -0.12 1.1 -0.82 1.7 -0.84 -0.087 -0.22 -0.17 -0.048 -0.44 -0.051 9e+03 0.14 1 0.48 +
2 -0.34 0.093 0.5 -0.78 -0.32 0.78 -0.51 2.7 -0.87 -0.039 -0.35 -0.23 -0.17 -0.64 -0.023 8.9e+03 0.11 1 0.27 +
3 -0.34 0.093 0.5 -0.78 -0.32 0.78 -0.51 2.7 -0.87 -0.039 -0.35 -0.23 -0.17 -0.64 -0.023 8.9e+03 0.11 0.5 -2.1 -
4 -0.34 0.093 0.5 -0.78 -0.32 0.78 -0.51 2.7 -0.87 -0.039 -0.35 -0.23 -0.17 -0.64 -0.023 8.9e+03 0.11 0.25 -0.019 -
5 -0.29 0.34 0.44 -0.85 -0.31 0.78 -0.55 2.7 -0.81 -0.07 -0.25 -0.15 -0.18 -0.63 -0.028 8.7e+03 0.029 0.25 0.86 +
6 -0.35 0.38 0.36 -0.91 -0.29 0.71 -0.59 2.4 -0.89 -0.19 -0.26 -0.13 -0.21 -0.76 -0.05 8.6e+03 0.0093 2.5 1.1 ++
7 -0.35 0.38 0.36 -0.91 -0.29 0.71 -0.59 2.4 -0.89 -0.19 -0.26 -0.13 -0.21 -0.76 -0.05 8.6e+03 0.0093 0.71 -0.59 -
8 -0.34 0.38 0.38 -1.2 -0.36 0.56 -0.63 1.7 -1.1 -0.29 -0.14 -0.1 -0.27 -0.77 -0.079 8.6e+03 0.026 7.1 0.9 ++
9 -0.56 0.64 0.51 -1.8 -0.49 0.46 -0.76 1 -1.5 -0.4 0.029 -0.087 -0.37 -1.2 -0.16 8.5e+03 0.039 7.1 0.8 +
10 -0.82 0.78 0.53 -2.2 -0.54 0.37 -0.78 1 -1.5 -0.44 0.082 -0.11 -0.4 -1.3 -0.17 8.4e+03 0.0087 71 1.1 ++
11 -0.81 0.9 0.76 -2.5 -0.7 0.21 -0.78 1 -1.6 -0.62 0.15 -0.096 -0.55 -1.4 -0.22 8.4e+03 0.0017 7.1e+02 1 ++
12 -0.81 0.9 0.76 -2.5 -0.7 0.21 -0.78 1 -1.6 -0.62 0.15 -0.096 -0.55 -1.4 -0.22 8.4e+03 5.2e-06 7.1e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000057
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost mu_public asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.78 -0.32 -0.016 -1 -0.58 -0.29 1.8 -0.08 -0.12 -0.011 1e+04 0.17 1 0.23 +
1 -0.78 -0.32 -0.016 -1 -0.58 -0.29 1.8 -0.08 -0.12 -0.011 1e+04 0.17 0.5 -0.055 -
2 -0.28 0.18 0.0029 -0.65 -0.44 -0.56 1.4 -0.075 -0.15 -0.02 8.8e+03 0.085 0.5 0.72 +
3 -0.69 0.45 0.5 -0.74 -0.45 -0.76 1.7 -0.18 -0.12 -0.32 8.5e+03 0.0093 5 0.92 ++
4 -0.69 0.45 0.5 -0.74 -0.45 -0.76 1.7 -0.18 -0.12 -0.32 8.5e+03 0.0093 0.36 0.0025 -
5 -0.74 0.55 0.49 -0.89 -0.62 -0.78 1.4 -0.0016 -0.12 -0.36 8.5e+03 0.0086 3.6 0.94 ++
6 -1.1 0.73 0.68 -0.9 -0.62 -0.84 1.1 0.032 -0.13 -0.62 8.5e+03 0.0071 36 1.1 ++
7 -1.3 0.83 0.79 -0.91 -0.63 -0.85 1.1 0.042 -0.11 -0.62 8.5e+03 0.0017 3.6e+02 1.2 ++
8 -1.4 0.89 0.85 -0.91 -0.65 -0.86 1 0.054 -0.11 -0.63 8.5e+03 0.00079 3.6e+03 1.1 ++
9 -1.4 0.89 0.85 -0.92 -0.64 -0.86 1 0.055 -0.11 -0.63 8.5e+03 7.2e-05 3.6e+04 1 ++
10 -1.4 0.89 0.85 -0.92 -0.64 -0.86 1 0.055 -0.11 -0.63 8.5e+03 3.4e-07 3.6e+04 1 ++
Considering neighbor 1/20 for current solution
Attempt 42/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000058
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car b_time_swissmet b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho
0 -0.42 0.29 -0.63 -0.11 -0.5 2 0.082 -0.29 -0.26 -0.23 -0.1 -0.38 0.15 -0.51 9.6e+03 0.36 1 0.61 +
1 -0.42 0.29 -0.63 -0.11 -0.5 2 0.082 -0.29 -0.26 -0.23 -0.1 -0.38 0.15 -0.51 9.6e+03 0.36 0.5 -2.1 -
2 -0.42 0.29 -0.63 -0.11 -0.5 2 0.082 -0.29 -0.26 -0.23 -0.1 -0.38 0.15 -0.51 9.6e+03 0.36 0.25 -0.54 -
3 -0.32 0.33 -0.49 -0.1 -0.45 2 -0.17 -0.32 -0.51 -0.26 -0.35 -0.25 0.17 -0.31 8.8e+03 0.19 0.25 0.7 +
4 -0.33 0.46 -0.6 -0.18 -0.52 2.2 -0.13 -0.38 -0.47 -0.21 -0.32 -0.5 0.2 -0.4 8.3e+03 0.036 2.5 0.91 ++
5 -0.59 0.88 -1.1 0.43 -0.51 2.3 -0.54 -0.15 -0.8 0.65 -0.52 -1.4 1.5 -0.53 8.1e+03 0.0076 25 1.1 ++
6 -0.61 1 -1.3 0.46 -0.69 1.5 -0.52 -0.36 -1 0.74 -0.65 -1.7 1.7 -0.63 8.1e+03 0.023 25 0.42 +
7 -0.63 1 -1.3 0.42 -0.72 1.6 -0.51 -0.43 -1 0.68 -0.62 -1.6 1.6 -0.64 8.1e+03 0.0011 2.5e+02 1 ++
8 -0.62 1 -1.3 0.42 -0.7 1.7 -0.52 -0.39 -1 0.68 -0.62 -1.6 1.6 -0.64 8.1e+03 0.00017 2.5e+03 1 ++
9 -0.62 1 -1.3 0.42 -0.7 1.7 -0.52 -0.39 -1 0.68 -0.62 -1.6 1.6 -0.64 8.1e+03 5.8e-07 2.5e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 43/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000059
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train lambda_travel_t b_cost_train mu_public b_time_swissmet b_cost_swissmet asc_car b_time_car b_cost_car Function Relgrad Radius Rho
0 0 0 1 0 1 0 0 0 0 0 1.1e+04 0.22 0.5 0.034 -
1 -0.5 -0.39 1 -0.46 1.4 -0.19 0.36 -0.06 -0.14 -0.11 9.4e+03 0.15 0.5 0.58 +
2 -0.38 -0.44 1.1 -0.44 1.4 -0.37 -0.14 -0.19 -0.29 -0.25 8.9e+03 0.053 0.5 0.85 +
3 -0.35 -0.83 1.1 -0.91 1.6 -0.8 -0.64 -0.43 -0.62 -0.53 8.6e+03 0.025 5 1 ++
4 -0.35 -0.83 1.1 -0.91 1.6 -0.8 -0.64 -0.43 -0.62 -0.53 8.6e+03 0.025 2.5 1 -
5 -0.35 -0.83 1.1 -0.91 1.6 -0.8 -0.64 -0.43 -0.62 -0.53 8.6e+03 0.025 1.2 -20 -
6 -0.35 -0.83 1.1 -0.91 1.6 -0.8 -0.64 -0.43 -0.62 -0.53 8.6e+03 0.025 0.62 -0.79 -
7 0.2 -1 0.72 -1.5 1.7 -1.1 -0.84 -0.43 -0.92 -0.58 8.4e+03 0.024 6.2 0.93 ++
8 0.38 -1.7 0.29 -1.7 1.2 -1.6 -0.8 -0.088 -1.2 -0.77 8.4e+03 0.025 62 0.94 ++
9 0.39 -2 0.27 -1.7 1.1 -1.7 -0.79 -0.0095 -1.4 -0.77 8.4e+03 0.0061 6.2e+02 1.2 ++
10 0.31 -2.1 0.27 -1.8 1 -1.6 -0.76 0.022 -1.4 -0.73 8.3e+03 0.0047 6.2e+03 1.2 ++
11 0.4 -2.3 0.16 -1.9 1 -1.7 -0.77 0.095 -1.5 -0.8 8.3e+03 0.00067 6.2e+04 0.98 ++
12 0.4 -2.3 0.16 -1.9 1 -1.7 -0.77 0.095 -1.5 -0.8 8.3e+03 5e-06 6.2e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 44/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000060
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di b_cost_train mu_public b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.2 -
1 -0.28 -0.47 -0.077 -0.28 1.5 0.19 0.076 0.22 -0.092 -0.24 -0.08 -0.13 9.8e+03 0.21 0.5 0.39 +
2 -0.13 -0.33 -0.12 -0.34 1.6 -0.24 0.14 -0.28 -0.19 -0.41 -0.18 -0.22 9.3e+03 0.26 0.5 0.49 +
3 -0.2 -0.52 -0.16 -0.75 2.1 -0.58 0.19 -0.35 -0.26 -0.56 -0.25 -0.3 8.6e+03 0.026 5 0.91 ++
4 -0.2 -0.52 -0.16 -0.75 2.1 -0.58 0.19 -0.35 -0.26 -0.56 -0.25 -0.3 8.6e+03 0.026 2.5 -84 -
5 -0.2 -0.52 -0.16 -0.75 2.1 -0.58 0.19 -0.35 -0.26 -0.56 -0.25 -0.3 8.6e+03 0.026 1.2 -16 -
6 -0.2 -0.52 -0.16 -0.75 2.1 -0.58 0.19 -0.35 -0.26 -0.56 -0.25 -0.3 8.6e+03 0.026 0.62 -0.73 -
7 0.078 -0.82 -0.056 -1.4 2.2 -0.96 0.3 -0.79 -0.53 -0.89 -0.31 -0.49 8.4e+03 0.012 6.2 1 ++
8 0.078 -0.82 -0.056 -1.4 2.2 -0.96 0.3 -0.79 -0.53 -0.89 -0.31 -0.49 8.4e+03 0.012 0.75 -0.82 -
9 0.072 -1 0.27 -1.7 1.8 -1.2 1 -0.97 -0.69 -0.99 0.26 -0.67 8.4e+03 0.017 7.5 1 ++
10 0.072 -1 0.27 -1.7 1.8 -1.2 1 -0.97 -0.69 -0.99 0.26 -0.67 8.4e+03 0.017 0.38 -0.23 -
11 0.029 -1.2 0.29 -1.6 1.4 -1.4 1.2 -0.79 -0.59 -1 0.3 -0.61 8.3e+03 0.02 3.8 1.1 ++
12 0.033 -1.4 0.4 -1.8 1.1 -1.7 1.6 -0.82 -0.6 -1.2 0.59 -0.68 8.3e+03 0.022 38 1.2 ++
13 0.0026 -1.5 0.36 -1.8 1 -1.7 1.6 -0.78 -0.58 -1.2 0.59 -0.67 8.3e+03 0.0046 3.8e+02 1.2 ++
14 -0.00079 -1.5 0.36 -1.8 1 -1.7 1.6 -0.78 -0.58 -1.2 0.59 -0.67 8.3e+03 0.0021 3.8e+03 1 ++
15 0.035 -1.5 0.35 -1.9 1 -1.8 1.6 -0.8 -0.57 -1.2 0.62 -0.69 8.3e+03 6.2e-05 3.8e+04 1 ++
16 0.035 -1.5 0.35 -1.9 1 -1.8 1.6 -0.8 -0.57 -1.2 0.62 -0.69 8.3e+03 2.6e-08 3.8e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 45/100
Considering neighbor 0/20 for current solution
Attempt 46/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000061
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.19 -
1 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.5 0.78 +
2 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.25 0.78 -
3 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.12 0.78 -
4 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.062 0.78 -
5 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.031 -59 -
6 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.016 -5.9 -
7 -0.29 0.016 -0.52 -0.084 0.01 -0.003 -0.054 1 0.19 0.062 -0.0082 -0.038 -0.014 -0.0059 9.5e+03 6.4 0.016 0.27 +
8 -0.29 0.018 -0.52 -0.087 0.011 0.0037 -0.059 1 0.19 0.065 -0.012 -0.04 -0.03 -0.015 9.4e+03 0.77 0.016 0.34 +
9 -0.29 0.018 -0.52 -0.087 0.011 0.0037 -0.059 1 0.19 0.065 -0.012 -0.04 -0.03 -0.015 9.4e+03 0.77 0.0078 -5.6 -
10 -0.29 0.018 -0.52 -0.087 0.011 0.0037 -0.059 1 0.19 0.065 -0.012 -0.04 -0.03 -0.015 9.4e+03 0.77 0.0039 -1.7 -
11 -0.29 0.022 -0.53 -0.09 0.015 -0.00025 -0.063 1 0.19 0.069 -0.016 -0.043 -0.034 -0.011 9.3e+03 0.17 0.039 0.91 ++
12 -0.3 0.036 -0.54 -0.094 0.029 -0.00088 -0.089 1 0.19 0.075 -0.034 -0.053 -0.073 -0.023 9.3e+03 0.88 0.39 0.96 ++
13 -0.3 0.036 -0.54 -0.094 0.029 -0.00088 -0.089 1 0.19 0.075 -0.034 -0.053 -0.073 -0.023 9.3e+03 0.88 0.2 -0.38 -
14 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.2 0.49 +
15 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.098 0.49 -
16 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.049 0.49 -
17 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.024 -6.4 -
18 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.012 -4.1 -
19 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.0061 -2.8 -
20 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.0031 -1.3 -
21 -0.32 0.13 -0.62 -0.12 0.096 -0.0017 -0.27 1.1 0.12 0.11 -0.11 -0.12 -0.26 -0.094 9.1e+03 5.5 0.0031 0.36 +
22 -0.32 0.13 -0.62 -0.12 0.094 -8.5e-05 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9.1e+03 3.3 0.0031 0.48 +
23 -0.32 0.13 -0.62 -0.12 0.094 -8.5e-05 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9.1e+03 3.3 0.0015 -1.3 -
24 -0.32 0.13 -0.62 -0.12 0.094 -8.5e-05 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9.1e+03 3.3 0.00076 -0.17 -
25 -0.32 0.13 -0.62 -0.12 0.094 -0.00085 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 2.5 0.00076 0.62 +
26 -0.32 0.13 -0.62 -0.12 0.094 -0.00085 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 2.5 0.00038 -1.1 -
27 -0.32 0.13 -0.62 -0.12 0.094 -0.00085 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 2.5 0.00019 -0.12 -
28 -0.32 0.13 -0.62 -0.12 0.093 -0.00066 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 0.78 0.00019 0.69 +
29 -0.32 0.13 -0.62 -0.12 0.093 -0.00068 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 0.095 0.0019 1 ++
30 -0.32 0.13 -0.62 -0.12 0.093 -0.00066 -0.27 1.1 0.11 0.11 -0.1 -0.12 -0.26 -0.096 9e+03 0.49 0.019 1 ++
31 -0.32 0.14 -0.62 -0.12 0.086 -0.00065 -0.28 1.1 0.095 0.11 -0.097 -0.12 -0.25 -0.097 9e+03 0.082 0.19 1 ++
32 -0.32 0.22 -0.64 -0.14 0.089 -0.00061 -0.39 1.1 -0.096 0.12 -0.063 -0.16 -0.22 -0.12 8.8e+03 0.2 1.9 0.96 ++
33 -0.32 0.22 -0.64 -0.14 0.089 -0.00061 -0.39 1.1 -0.096 0.12 -0.063 -0.16 -0.22 -0.12 8.8e+03 0.2 0.95 -4.9 -
34 -0.32 0.22 -0.64 -0.14 0.089 -0.00061 -0.39 1.1 -0.096 0.12 -0.063 -0.16 -0.22 -0.12 8.8e+03 0.2 0.48 -0.33 -
35 -0.32 0.53 -0.68 -0.19 0.43 -0.0021 -0.66 1.1 -0.57 0.18 -0.17 -0.3 -0.55 -0.22 8.5e+03 3.8 0.48 0.54 +
36 -0.58 1 -0.67 -0.19 0.26 -0.0013 -0.75 1.2 -0.58 0.63 -0.3 -0.51 -0.47 -0.11 8.3e+03 4 4.8 0.91 ++
37 -0.58 1 -0.67 -0.19 0.26 -0.0013 -0.75 1.2 -0.58 0.63 -0.3 -0.51 -0.47 -0.11 8.3e+03 4 2.4 0.91 -
38 -0.58 1 -0.67 -0.19 0.26 -0.0013 -0.75 1.2 -0.58 0.63 -0.3 -0.51 -0.47 -0.11 8.3e+03 4 1.2 -4e+02 -
39 -0.58 1 -0.67 -0.19 0.26 -0.0013 -0.75 1.2 -0.58 0.63 -0.3 -0.51 -0.47 -0.11 8.3e+03 4 0.6 -38 -
40 -1.2 1.4 -0.53 0.061 0.41 -0.0019 -0.79 1.3 -0.94 0.61 -0.69 -0.86 -0.46 0.16 8.3e+03 1.5 0.6 0.19 +
41 -1.2 1.4 -0.53 0.061 0.41 -0.0019 -0.79 1.3 -0.94 0.61 -0.69 -0.86 -0.46 0.16 8.3e+03 1.5 0.3 -0.1 -
42 -1.2 1.4 -0.52 0.051 0.39 -0.0019 -0.77 1.2 -0.78 0.9 -0.58 -0.88 -0.42 0.15 8.2e+03 0.45 0.3 0.64 +
43 -1.2 1.4 -0.52 0.051 0.39 -0.0019 -0.77 1.2 -0.78 0.9 -0.58 -0.88 -0.42 0.15 8.2e+03 0.45 0.12 0.052 -
44 -1.2 1.3 -0.56 0.087 0.37 -0.0018 -0.76 1.2 -0.84 0.79 -0.56 -0.88 -0.48 0.24 8.2e+03 0.16 0.12 0.81 +
45 -1.1 1.4 -0.66 0.05 0.32 -0.0016 -0.75 1.1 -0.91 0.86 -0.51 -0.93 -0.53 0.18 8.2e+03 0.079 1.2 1.1 ++
46 -1.1 1.4 -0.66 0.05 0.32 -0.0016 -0.75 1.1 -0.91 0.86 -0.51 -0.93 -0.53 0.18 8.2e+03 0.079 0.16 -0.47 -
47 -1.2 1.5 -0.82 0.044 0.18 -0.001 -0.75 1 -1.1 0.98 -0.46 -0.99 -0.67 0.28 8.2e+03 0.063 1.6 0.96 ++
48 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 16 1 ++
49 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 8.1 1 -
50 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 4 1 -
51 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 2 -1.1e+03 -
52 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 1 -3.8e+02 -
53 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 0.5 -80 -
54 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 0.25 -4.9 -
55 -1.2 1.6 -1.1 0.081 0.03 -0.00041 -0.74 1 -1.3 1.1 -0.47 -1 -0.87 0.31 8.2e+03 1.5 0.25 0.31 +
56 -1.2 1.6 -1.1 0.08 0.063 -0.00053 -0.74 1 -1.3 1.1 -0.47 -1 -0.88 0.31 8.2e+03 0.073 2.5 1 ++
57 -1.2 1.6 -1.1 0.08 0.063 -0.00053 -0.74 1 -1.3 1.1 -0.47 -1 -0.88 0.31 8.2e+03 0.073 1.3 -3.7e+02 -
58 -1.2 1.6 -1.1 0.08 0.063 -0.00053 -0.74 1 -1.3 1.1 -0.47 -1 -0.88 0.31 8.2e+03 0.073 0.63 -47 -
59 -1.2 1.6 -1.1 0.08 0.063 -0.00053 -0.74 1 -1.3 1.1 -0.47 -1 -0.88 0.31 8.2e+03 0.073 0.32 -2.3 -
60 -1.1 1.5 -1.4 0.13 -0.015 -0.0002 -0.76 1 -1.6 1.4 -0.38 -1 -1.1 0.31 8.1e+03 0.14 0.32 0.83 +
61 -1.1 1.5 -1.4 0.14 -0.00017 -0.00026 -0.76 1 -1.6 1.3 -0.39 -1 -1.2 0.31 8.1e+03 0.026 3.2 1 ++
62 -1.1 1.5 -1.4 0.14 -0.00017 -0.00026 -0.76 1 -1.6 1.3 -0.39 -1 -1.2 0.31 8.1e+03 0.026 1 -1.4e+02 -
63 -1.1 1.5 -1.4 0.14 -0.00017 -0.00026 -0.76 1 -1.6 1.3 -0.39 -1 -1.2 0.31 8.1e+03 0.026 0.51 -14 -
64 -1.1 1.5 -1.4 0.14 -0.00017 -0.00026 -0.76 1 -1.6 1.3 -0.39 -1 -1.2 0.31 8.1e+03 0.026 0.25 0.062 -
65 -0.96 1.6 -1.7 0.16 -0.04 -9.9e-05 -0.78 1 -1.8 1.3 -0.43 -1 -1.3 0.36 8.1e+03 0.18 2.5 1.1 ++
66 -0.96 1.6 -1.7 0.16 -0.04 -9.9e-05 -0.78 1 -1.8 1.3 -0.43 -1 -1.3 0.36 8.1e+03 0.18 0.67 -21 -
67 -0.96 1.6 -1.7 0.16 -0.04 -9.9e-05 -0.78 1 -1.8 1.3 -0.43 -1 -1.3 0.36 8.1e+03 0.18 0.33 -1.6 -
68 -0.88 1.5 -2 0.11 -0.084 9e-05 -0.76 1 -2.1 1.3 -0.36 -0.99 -1.6 0.27 8.1e+03 0.87 3.3 0.92 ++
69 -0.88 1.5 -2 0.11 -0.075 5.5e-05 -0.76 1 -2.1 1.3 -0.36 -0.99 -1.6 0.27 8.1e+03 0.27 33 1 ++
70 -0.88 1.5 -2 0.11 -0.075 5.5e-05 -0.76 1 -2.1 1.3 -0.36 -0.99 -1.6 0.27 8.1e+03 0.27 0.37 -2.5 -
71 -0.67 1.6 -2.4 0.045 -0.1 0.00016 -0.76 1 -2.4 1.1 -0.39 -1 -1.7 0.17 8.1e+03 3.2 0.37 0.87 +
72 -0.53 1.6 -2.5 -0.13 -0.1 0.00018 -0.75 1 -2.4 0.81 -0.34 -1 -1.8 -0.026 8.1e+03 1.1 3.7 1 ++
73 -0.58 1.6 -2.4 -0.27 -0.1 0.00017 -0.74 1 -2.4 0.61 -0.35 -1 -1.8 -0.19 8.1e+03 0.39 37 0.98 ++
74 -0.58 1.6 -2.5 -0.27 -0.1 0.00017 -0.75 1 -2.4 0.59 -0.35 -1 -1.8 -0.21 8.1e+03 0.029 3.7e+02 0.99 ++
75 -0.57 1.6 -2.5 -0.29 -0.1 0.00017 -0.74 1 -2.4 0.56 -0.34 -1 -1.8 -0.23 8.1e+03 0.00035 3.7e+03 1 ++
76 -0.57 1.6 -2.5 -0.29 -0.1 0.00017 -0.74 1 -2.4 0.55 -0.34 -1 -1.8 -0.24 8.1e+03 0.024 3.7e+04 1 ++
77 -0.57 1.6 -2.5 -0.29 -0.1 0.00017 -0.74 1 -2.4 0.55 -0.34 -1 -1.8 -0.24 8.1e+03 7.3e-05 3.7e+05 1 ++
78 -0.57 1.6 -2.5 -0.29 -0.1 0.00017 -0.74 1 -2.4 0.55 -0.34 -1 -1.8 -0.24 8.1e+03 5.9e-06 3.7e+05 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 20 unknown parameters [max: 50]
*** Estimate b07everything_000062
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.59 -
1 1.1e+04 0.4 0.25 0.01 -
2 9.6e+03 1.1 0.25 0.79 +
3 9.6e+03 1.1 0.12 0.79 -
4 9.6e+03 1.1 0.062 0.79 -
5 9.6e+03 1.1 0.031 -14 -
6 9.6e+03 1.1 0.016 -1.6 -
7 9.4e+03 0.54 0.16 0.97 ++
8 9.1e+03 0.11 1.6 0.99 ++
9 9.1e+03 0.11 0.78 -2.7 -
10 9.1e+03 0.11 0.39 -0.77 -
11 8.9e+03 6.4 0.39 0.25 +
12 8.9e+03 6.4 0.2 0.25 -
13 8.9e+03 6.4 0.098 0.25 -
14 8.9e+03 6.4 0.049 0.25 -
15 8.9e+03 6.4 0.024 0.25 -
16 8.9e+03 6.4 0.012 0.25 -
17 8.9e+03 6.4 0.0061 -1.1 -
18 8.8e+03 14 0.0061 0.28 +
19 8.7e+03 6.2 0.0061 0.14 +
20 8.7e+03 6.2 0.0031 -0.51 -
21 8.5e+03 4.7 0.0031 0.79 +
22 8.5e+03 4.7 0.0015 -1.3 -
23 8.5e+03 4.7 0.00076 -0.6 -
24 8.5e+03 4.7 0.00038 0.099 -
25 8.5e+03 1.8 0.0038 0.97 ++
26 8.5e+03 0.35 0.038 1 ++
27 8.4e+03 0.041 0.38 0.99 ++
28 8.2e+03 0.28 3.8 0.91 ++
29 8.2e+03 0.28 1.9 0.91 -
30 8.2e+03 0.28 0.95 -99 -
31 8.2e+03 0.28 0.48 -40 -
32 8.2e+03 0.28 0.24 -7.3 -
33 8.2e+03 0.76 0.24 0.25 +
34 8.1e+03 1.5 2.4 0.97 ++
35 8.1e+03 1.5 1.2 -1.3e+02 -
36 8.1e+03 1.5 0.6 -21 -
37 8.1e+03 1.5 0.3 -3.2 -
38 8.1e+03 11 0.3 0.26 +
39 8e+03 0.31 3 0.96 ++
40 8e+03 3.8 30 0.94 ++
41 8e+03 0.089 3e+02 1 ++
42 8e+03 0.00028 3e+03 1 ++
43 8e+03 2.2e-06 3e+03 1 ++
Considering neighbor 1/20 for current solution
Attempt 47/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000063
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_cost_car b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho
0 -0.72 -0.0095 -0.01 -0.68 1.4 -0.65 2 0.14 -0.14 -0.029 -0.45 -0.1 -0.65 -0.67 9.8e+03 0.24 1 0.49 +
1 -0.72 -0.0095 -0.01 -0.68 1.4 -0.65 2 0.14 -0.14 -0.029 -0.45 -0.1 -0.65 -0.67 9.8e+03 0.24 0.5 -2.9 -
2 -0.72 -0.0095 -0.01 -0.68 1.4 -0.65 2 0.14 -0.14 -0.029 -0.45 -0.1 -0.65 -0.67 9.8e+03 0.24 0.25 -0.031 -
3 -0.56 0.12 -0.005 -0.61 1.4 -0.58 1.9 -0.11 -0.34 -0.037 -0.64 -0.35 -0.66 -0.42 8.6e+03 0.048 0.25 0.86 +
4 -0.45 0.28 0.036 -0.8 1.1 -0.81 2.1 -0.17 -0.18 -0.09 -0.52 -0.38 -0.79 -0.44 8.4e+03 0.017 2.5 1.1 ++
5 0.071 0.38 0.21 -1.8 -0.2 -0.84 2.3 0.23 -0.047 -0.49 -1.2 -0.55 -1.8 -0.53 8.3e+03 0.061 2.5 0.26 +
6 0.07 0.45 0.2 -2.1 -0.036 -1 1.9 0.3 -0.064 -0.52 -1.3 -0.7 -1.5 -0.57 8.2e+03 0.0094 25 1 ++
7 -0.0089 0.47 0.22 -2 0.12 -1 1.8 0.24 -0.057 -0.48 -1.2 -0.69 -1.5 -0.58 8.2e+03 0.00072 2.5e+02 1 ++
8 -0.02 0.48 0.22 -2 0.13 -1.1 1.8 0.23 -0.057 -0.48 -1.2 -0.68 -1.5 -0.59 8.2e+03 2.2e-05 2.5e+03 1 ++
9 -0.02 0.48 0.22 -2 0.13 -1.1 1.8 0.23 -0.057 -0.48 -1.2 -0.68 -1.5 -0.59 8.2e+03 9.8e-08 2.5e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000064
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 0.26 0.11 -0.69 -0.45 -0.73 -0.84 -0.59 -0.65 -0.072 -0.17 -0.43 -0.58 8.6e+03 0.077 10 1.1 ++
1 -0.96 0.67 0.6 -1.1 -0.68 -0.84 -1 -0.82 -0.54 -0.099 -0.54 -0.58 -0.73 8.4e+03 0.022 1e+02 1.2 ++
2 -0.93 0.84 0.75 -1.3 -0.79 -0.86 -1.1 -0.87 -0.56 -0.099 -0.56 -0.58 -0.77 8.4e+03 0.0032 1e+03 1.1 ++
3 -0.92 0.86 0.77 -1.3 -0.8 -0.86 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 6.6e-05 1e+04 1 ++
4 -0.92 0.86 0.77 -1.3 -0.8 -0.86 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 5e-08 1e+04 1 ++
Considering neighbor 1/20 for current solution
Attempt 48/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000065
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 -0.81 0.35 0.31 -0.87 0.36 -0.88 -0.7 -0.44 0.011 -0.32 -0.54 8.7e+03 0.054 10 1.1 ++
1 -0.7 0.63 0.55 -1.2 0.036 -1.4 -0.78 -0.35 -0.091 -0.52 -0.39 8.4e+03 0.02 1e+02 1.2 ++
2 -0.69 0.76 0.66 -1.3 -0.12 -1.7 -0.81 -0.36 -0.097 -0.55 -0.37 8.4e+03 0.0035 1e+03 1.1 ++
3 -0.69 0.77 0.67 -1.3 -0.14 -1.8 -0.82 -0.37 -0.098 -0.55 -0.37 8.4e+03 9.7e-05 1e+04 1 ++
4 -0.69 0.77 0.67 -1.3 -0.14 -1.8 -0.82 -0.37 -0.098 -0.55 -0.37 8.4e+03 7.6e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 49/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000066
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train square_tt_coef cube_tt_coef b_cost b_time_swissmet asc_car b_time_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.16 -
1 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.5 0.8 +
2 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.25 -10 -
3 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.12 -12 -
4 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.062 -14 -
5 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.031 -16 -
6 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.016 -5.2 -
7 -0.29 -0.52 0.017 -0.0028 -0.054 0.19 -0.0082 -0.014 9.5e+03 5.2 0.016 0.36 +
8 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.016 0.66 +
9 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.0078 -0.85 -
10 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.0039 -0.93 -
11 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.002 -1.2 -
12 -0.29 -0.53 0.021 -0.0012 -0.063 0.19 -0.016 -0.031 9.4e+03 1.1 0.002 0.6 +
13 -0.29 -0.53 0.022 -0.00093 -0.064 0.19 -0.017 -0.033 9.4e+03 0.34 0.02 1.1 ++
14 -0.29 -0.53 0.03 -0.00065 -0.078 0.19 -0.026 -0.053 9.3e+03 0.11 0.2 1 ++
15 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.2 0.64 +
16 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.098 -8.6 -
17 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.049 -8.9 -
18 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.024 -11 -
19 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.012 -5.2 -
20 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.0061 -3.5 -
21 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.0031 -2.1 -
22 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.0015 -0.54 -
23 -0.33 -0.63 0.11 -0.0013 -0.23 0.17 -0.11 -0.25 9.2e+03 2.1 0.0015 0.45 +
24 -0.33 -0.63 0.11 -0.0004 -0.23 0.16 -0.11 -0.25 9.2e+03 2.5 0.0015 0.28 +
25 -0.33 -0.63 0.11 -0.0004 -0.23 0.16 -0.11 -0.25 9.2e+03 2.5 0.00076 -0.39 -
26 -0.33 -0.63 0.11 -0.0012 -0.23 0.16 -0.11 -0.24 9.2e+03 1.8 0.00076 0.21 +
27 -0.33 -0.63 0.11 -0.0012 -0.23 0.16 -0.11 -0.24 9.2e+03 1.8 0.00038 0.023 -
28 -0.33 -0.63 0.11 -0.00078 -0.23 0.16 -0.11 -0.24 9.2e+03 0.1 0.00038 0.89 +
29 -0.33 -0.63 0.11 -0.00071 -0.23 0.16 -0.11 -0.24 9.2e+03 0.95 0.0038 0.97 ++
30 -0.33 -0.63 0.11 -0.00077 -0.24 0.16 -0.1 -0.24 9.2e+03 0.098 0.038 1 ++
31 -0.33 -0.63 0.092 -0.00067 -0.26 0.12 -0.093 -0.22 9.1e+03 0.22 0.38 1 ++
32 -0.34 -0.72 0.19 -0.00095 -0.53 -0.26 -0.083 -0.28 8.8e+03 1.9 0.38 0.8 +
33 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.38 0.44 +
34 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.19 -5.4 -
35 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.095 -5.9 -
36 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.048 -7.3 -
37 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.024 -5.5 -
38 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.012 -4.1 -
39 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.006 -3.5 -
40 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.003 -3.1 -
41 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.0015 -2.7 -
42 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.00075 -2.1 -
43 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.00037 -0.88 -
44 -0.32 -0.71 0.48 -0.0022 -0.72 -0.64 -0.2 -0.53 8.7e+03 0.06 0.0037 0.91 ++
45 -0.32 -0.71 0.48 -0.0023 -0.72 -0.64 -0.2 -0.52 8.7e+03 1.2 0.037 1 ++
46 -0.33 -0.72 0.45 -0.0021 -0.72 -0.64 -0.2 -0.49 8.7e+03 0.87 0.37 1 ++
47 -0.5 -0.91 0.079 -0.00062 -0.77 -0.79 -0.51 -0.56 8.7e+03 0.6 0.37 0.4 +
48 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 3.7 1.1 ++
49 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 1.9 -1.6e+02 -
50 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 0.93 -68 -
51 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 0.47 -8.8 -
52 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 0.23 -0.023 -
53 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.23 0.69 +
54 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.12 -2.5 -
55 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.058 -2.5 -
56 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.029 -2.3 -
57 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.015 -2.3 -
58 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.0073 -2.5 -
59 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.0036 -2.7 -
60 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.0018 -2.8 -
61 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.00091 -2.9 -
62 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.00045 -1.5 -
63 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.00023 -0.4 -
64 -0.4 -1.5 -0.026 -0.00028 -0.77 -1.3 -0.5 -0.88 8.6e+03 5.2 0.00023 0.17 +
65 -0.4 -1.5 -0.026 -0.00028 -0.77 -1.3 -0.5 -0.88 8.6e+03 5.2 0.00011 -0.57 -
66 -0.4 -1.5 -0.026 -0.00016 -0.77 -1.3 -0.5 -0.88 8.6e+03 0.62 0.0011 0.96 ++
67 -0.4 -1.5 -0.025 -0.00016 -0.77 -1.3 -0.5 -0.88 8.6e+03 0.036 0.011 1 ++
68 -0.4 -1.5 -0.014 -0.00021 -0.77 -1.3 -0.51 -0.88 8.6e+03 0.044 0.11 1 ++
69 -0.33 -1.6 -0.0048 -0.00025 -0.77 -1.4 -0.52 -0.96 8.6e+03 0.024 1.1 0.99 ++
70 -0.33 -1.6 -0.0048 -0.00025 -0.77 -1.4 -0.52 -0.96 8.6e+03 0.024 0.57 -6.2 -
71 -0.33 -1.6 -0.0048 -0.00025 -0.77 -1.4 -0.52 -0.96 8.6e+03 0.024 0.28 -0.12 -
72 -0.28 -1.9 -0.074 4.3e-05 -0.77 -1.5 -0.53 -1.1 8.5e+03 2.3 0.28 0.8 +
73 -0.11 -2.1 -0.064 7.6e-06 -0.78 -1.8 -0.53 -1.3 8.5e+03 0.12 2.8 0.99 ++
74 -0.11 -2.1 -0.064 7.6e-06 -0.78 -1.8 -0.53 -1.3 8.5e+03 0.12 0.65 -5.4 -
75 -0.11 -2.1 -0.064 7.6e-06 -0.78 -1.8 -0.53 -1.3 8.5e+03 0.12 0.33 -0.13 -
76 -0.0096 -2.4 -0.1 0.00017 -0.78 -2 -0.52 -1.5 8.5e+03 6.7 0.33 0.77 +
77 0.2 -2.8 -0.099 0.00017 -0.8 -2.2 -0.52 -1.6 8.5e+03 1.4 3.3 1 ++
78 0.35 -3 -0.11 0.00021 -0.8 -2.4 -0.49 -1.7 8.5e+03 1.6 33 0.93 ++
79 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 0.028 3.3e+02 1 ++
80 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 0.00016 3.3e+03 1 ++
81 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 7.3e-06 3.3e+04 1 ++
82 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 2.7e-06 3.3e+04 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000067
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 0 -
1 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.25 -0.1 -
2 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 2.5 1 ++
3 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 1.2 1 -
4 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 0.62 -4.1 -
5 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 0.31 -2.5 -
6 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 0.16 -0.25 -
7 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.16 0.26 +
8 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.078 -0.8 -
9 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.039 -0.71 -
10 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.02 -0.65 -
11 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.0098 -0.55 -
12 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.0049 -0.098 -
13 -0.36 -0.41 -0.084 0.12 0.0011 -0.36 1.1 0.23 0.032 0.012 9.2e+03 5.2 0.0049 0.33 +
14 -0.36 -0.41 -0.084 0.12 0.0011 -0.36 1.1 0.23 0.032 0.012 9.2e+03 5.2 0.0024 -0.54 -
15 -0.36 -0.41 -0.081 0.12 -0.0013 -0.36 1.1 0.23 0.033 0.014 9.1e+03 4.7 0.0024 0.61 +
16 -0.36 -0.42 -0.082 0.12 -0.00087 -0.36 1.1 0.23 0.033 0.014 9.1e+03 2.7 0.024 1.3 ++
17 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.024 0.26 +
18 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.012 -2.4 -
19 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.0061 -2 -
20 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.0031 -1.6 -
21 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.0015 -0.97 -
22 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.00076 -0.23 -
23 -0.37 -0.43 -0.086 0.13 -0.0011 -0.37 1.1 0.2 0.036 0.017 9.1e+03 3 0.00076 0.43 +
24 -0.37 -0.43 -0.086 0.13 -0.0011 -0.37 1.1 0.2 0.036 0.017 9.1e+03 3 0.00038 -0.75 -
25 -0.37 -0.43 -0.087 0.13 -0.00069 -0.37 1.1 0.2 0.036 0.017 9.1e+03 5 0.00038 0.38 +
26 -0.37 -0.43 -0.087 0.13 -0.00069 -0.37 1.1 0.2 0.036 0.017 9.1e+03 5 0.00019 -0.2 -
27 -0.37 -0.44 -0.087 0.13 -0.00088 -0.37 1.1 0.2 0.036 0.017 9e+03 2.6 0.00019 0.33 +
28 -0.37 -0.44 -0.087 0.13 -0.00088 -0.37 1.1 0.2 0.036 0.017 9e+03 2.6 9.5e-05 -0.52 -
29 -0.37 -0.44 -0.087 0.13 -0.00079 -0.37 1.1 0.2 0.036 0.017 9e+03 0.96 9.5e-05 0.66 +
30 -0.37 -0.44 -0.087 0.13 -0.0008 -0.37 1.1 0.2 0.036 0.017 9e+03 0.064 0.00095 1 ++
31 -0.37 -0.44 -0.087 0.13 -0.00081 -0.37 1.1 0.2 0.036 0.017 9e+03 0.29 0.0095 1 ++
32 -0.37 -0.44 -0.088 0.13 -0.00082 -0.37 1.1 0.19 0.037 0.018 9e+03 0.063 0.095 1 ++
33 -0.38 -0.51 -0.097 0.17 -0.00097 -0.41 1.1 0.098 0.036 0.02 8.9e+03 0.18 0.95 0.99 ++
34 -0.28 -0.94 -0.13 -0.17 0.00042 -1.4 1.3 -0.77 -0.57 -0.37 8.7e+03 17 0.95 0.44 +
35 -0.28 -0.94 -0.13 -0.17 0.00042 -1.4 1.3 -0.77 -0.57 -0.37 8.7e+03 17 0.48 -0.59 -
36 -0.086 -1.4 -0.25 0.039 -0.00037 -1.3 1.4 -0.84 -0.56 -0.39 8.6e+03 20 0.48 0.17 +
37 -0.086 -1.4 -0.25 0.039 -0.00037 -1.3 1.4 -0.84 -0.56 -0.39 8.6e+03 20 0.24 -5.3 -
38 -0.086 -1.4 -0.25 0.039 -0.00037 -1.3 1.4 -0.84 -0.56 -0.39 8.6e+03 20 0.12 -0.64 -
39 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.12 0.45 +
40 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.06 -0.88 -
41 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.03 -0.82 -
42 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.015 -0.52 -
43 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.0075 -0.4 -
44 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.0037 -0.35 -
45 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.0019 -0.33 -
46 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.00093 -0.32 -
47 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.00047 -0.17 -
48 -0.07 -1.4 -0.25 -0.08 0.00024 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 17 0.00047 0.42 +
49 -0.07 -1.4 -0.25 -0.08 0.00024 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 17 0.00023 -0.67 -
50 -0.071 -1.4 -0.25 -0.08 2.8e-06 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 19 0.00023 0.39 +
51 -0.071 -1.4 -0.25 -0.08 2.8e-06 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 19 0.00012 -0.023 -
52 -0.071 -1.4 -0.25 -0.08 0.00012 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 15 0.00012 0.34 +
53 -0.071 -1.4 -0.25 -0.08 0.00012 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 15 5.8e-05 -0.32 -
54 -0.071 -1.4 -0.25 -0.08 6.1e-05 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 8.1 5.8e-05 0.51 +
55 -0.071 -1.4 -0.25 -0.08 7.9e-05 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 2.9 5.8e-05 0.75 +
56 -0.071 -1.4 -0.25 -0.08 7.4e-05 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 0.058 0.00058 0.99 ++
57 -0.071 -1.4 -0.25 -0.079 7.2e-05 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 0.14 0.0058 1 ++
58 -0.071 -1.4 -0.25 -0.073 4.6e-05 -1.3 1.4 -0.86 -0.55 -0.38 8.4e+03 0.17 0.058 1 ++
59 -0.068 -1.4 -0.26 -0.083 8.8e-05 -1.4 1.4 -0.8 -0.55 -0.38 8.4e+03 0.44 0.58 1 ++
60 0.35 -2 -0.85 -0.13 0.00032 -1.7 1.4 -0.85 -0.36 -0.46 8.4e+03 18 0.58 0.38 +
61 0.37 -2.2 -1 -0.098 0.00018 -1.8 1 -0.86 -0.31 -0.32 8.3e+03 30 0.58 0.47 +
62 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.58 0.23 +
63 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.29 -1.5 -
64 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.15 -1.1 -
65 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.073 -0.98 -
66 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.036 -0.93 -
67 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.018 -0.83 -
68 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.0091 -0.75 -
69 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.0045 -0.71 -
70 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.0023 -0.72 -
71 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.0011 -0.74 -
72 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.00057 -0.74 -
73 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.00028 -0.75 -
74 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.00014 -0.58 -
75 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 7.1e-05 -0.1 -
76 0.27 -2.2 -1.1 -0.11 0.00027 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 17 7.1e-05 0.35 +
77 0.27 -2.2 -1.1 -0.11 0.00023 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 2.7 0.00071 0.95 ++
78 0.27 -2.2 -1.1 -0.11 0.00023 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 0.07 0.0071 1 ++
79 0.27 -2.2 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.27 -0.33 8.3e+03 1.8 0.071 0.96 ++
80 0.28 -2.2 -1.1 -0.11 0.00021 -2 1 -0.81 -0.26 -0.36 8.3e+03 0.028 0.71 1 ++
81 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.0054 7.1 1 ++
82 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.013 71 1 ++
83 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.00073 7.1e+02 1 ++
84 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.0016 7.1e+03 1 ++
85 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.00092 7.1e+04 1 ++
86 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.00015 7.1e+05 1 ++
87 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 1.1e-05 7.1e+06 1 ++
88 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 6.6e-06 7.1e+07 1.1 ++
89 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 6.6e-06 1.9e-08 0 -
90 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 6.6e-06 9.7e-09 -5 -
Considering neighbor 1/20 for current solution
Attempt 50/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000068
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train b_cost mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car b_time_swissmet Function Relgrad Radius Rho
0 -0.46 0.42 0.082 0.0028 -0.73 -1 1.9 0.11 -0.3 -0.099 -0.024 -0.23 -0.42 9.1e+03 0.25 1 0.71 +
1 -0.38 0.66 0.25 0.036 -0.85 0 2.2 -0.22 -0.31 -0.12 -0.074 -0.61 -0.77 8.6e+03 0.11 1 0.55 +
2 -0.69 0.64 0.18 0.031 -0.8 -0.5 3.2 -0.52 0.044 0.022 -0.41 -0.57 -1 8.3e+03 0.029 1 0.77 +
3 -0.68 0.7 0.18 -0.094 -1.2 -0.58 2.2 -0.61 -0.2 -0.026 -0.3 -0.82 -1.4 8.2e+03 0.012 10 1 ++
4 -0.77 0.89 0.29 0.16 -1.2 -0.61 1.7 -0.5 -0.3 -0.034 -0.3 -0.86 -1.3 8.2e+03 0.0097 1e+02 1.1 ++
5 -0.87 0.93 0.34 0.24 -1.2 -0.62 1.7 -0.49 -0.38 -0.04 -0.34 -0.87 -1.3 8.2e+03 0.00051 1e+03 1 ++
6 -0.88 0.94 0.35 0.25 -1.2 -0.62 1.7 -0.49 -0.4 -0.04 -0.34 -0.87 -1.3 8.2e+03 5e-05 1e+04 1 ++
7 -0.88 0.94 0.35 0.25 -1.2 -0.62 1.7 -0.49 -0.4 -0.04 -0.34 -0.87 -1.3 8.2e+03 1.1e-07 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 51/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000069
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di b_cost_train mu_existing asc_car b_time_car_ref b_time_car_diff b_cost_car b_time_swissmet b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho
0 -0.45 -0.75 -0.052 -1 1.9 0.088 -0.67 -0.35 -0.35 -0.85 0.21 -0.75 9.1e+03 0.26 1 0.69 +
1 -0.45 -0.75 -0.052 -1 1.9 0.088 -0.67 -0.35 -0.35 -0.85 0.21 -0.75 9.1e+03 0.26 0.5 -0.98 -
2 -0.028 -0.78 -0.34 -1 2.3 -0.41 -0.64 -0.051 -0.45 -1.1 0.37 -0.25 8.4e+03 0.074 0.5 0.73 +
3 -0.063 -1.1 0.11 -0.88 2.2 -0.38 -0.79 0.12 -0.59 -1.3 0.87 -0.5 8.3e+03 0.013 5 1 ++
4 -0.065 -1.3 0.57 -1.1 1.9 -0.45 -0.95 0.76 -0.62 -1.6 1.8 -0.58 8.2e+03 0.0052 50 0.91 ++
5 -0.053 -1.3 0.49 -1.1 1.8 -0.47 -0.98 0.7 -0.64 -1.6 1.6 -0.61 8.2e+03 0.00078 5e+02 1.1 ++
6 -0.044 -1.3 0.48 -1.2 1.8 -0.46 -0.99 0.68 -0.63 -1.6 1.6 -0.61 8.2e+03 2.6e-05 5e+03 1 ++
7 -0.044 -1.3 0.48 -1.2 1.8 -0.46 -0.99 0.68 -0.63 -1.6 1.6 -0.61 8.2e+03 7.4e-08 5e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000070
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost mu_existing asc_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 1.1e+04 0.26 0.5 -0.48 -
1 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 5 0.99 ++
2 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 2.5 0.99 -
3 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 1.2 0.99 -
4 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.62 0.99 -
5 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.31 0.99 -
6 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.16 0.99 -
7 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.078 0.99 -
8 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.039 0.99 -
9 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.02 0.99 -
10 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.0098 0.99 -
11 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.0049 -3.8 -
12 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.0024 -2.8 -
13 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.0012 -2 -
14 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.00061 -1.1 -
15 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.00031 -0.17 -
16 -0.5 -0.5 -0.5 0.00031 -0.00031 -0.18 1.5 0.13 8.7e+03 4.3 0.00031 0.61 +
17 -0.5 -0.5 -0.5 0.00061 -0.00019 -0.18 1.5 0.13 8.7e+03 5.1 0.00031 0.19 +
18 -0.5 -0.5 -0.5 0.00092 -0.00027 -0.18 1.5 0.13 8.7e+03 2.5 0.00031 0.62 +
19 -0.5 -0.5 -0.5 0.0012 -0.00024 -0.18 1.5 0.13 8.7e+03 0.68 0.0031 0.91 ++
20 -0.5 -0.5 -0.5 0.0043 -0.00026 -0.19 1.5 0.13 8.7e+03 0.062 0.031 1 ++
21 -0.5 -0.52 -0.51 0.035 -0.00038 -0.21 1.5 0.12 8.7e+03 0.77 0.31 1 ++
22 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 3.1 1 ++
23 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 1.5 1 -
24 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 0.76 -1.4e+02 -
25 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 0.38 -27 -
26 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 0.19 -2.4 -
27 -0.51 -0.74 -0.55 -0.033 -0.0001 -0.71 1.7 0.01 8.5e+03 0.62 0.19 0.83 +
28 -0.44 -0.93 -0.62 -0.068 1.7e-05 -0.71 1.8 -0.029 8.4e+03 9.3 1.9 1.1 ++
29 -0.44 -0.93 -0.62 -0.068 1.7e-05 -0.71 1.8 -0.029 8.4e+03 9.3 0.25 0.045 -
30 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.25 0.72 +
31 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.11 -1.8 -
32 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.053 -1.5 -
33 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.026 -1.4 -
34 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.013 -1.5 -
35 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.0066 -1.3 -
36 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.0033 -1.2 -
37 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.0017 -1.2 -
38 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.00083 -1.3 -
39 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.00041 -1.4 -
40 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.00021 -1.5 -
41 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.0001 -1.5 -
42 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 5.2e-05 -1.5 -
43 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 2.6e-05 -0.015 -
44 -0.31 -1.2 -0.68 -0.098 0.00018 -0.67 2 0.092 8.4e+03 3.1 2.6e-05 0.85 +
45 -0.31 -1.2 -0.68 -0.098 0.00017 -0.67 2 0.092 8.4e+03 0.26 0.00026 0.95 ++
46 -0.31 -1.2 -0.68 -0.098 0.00017 -0.67 2 0.092 8.4e+03 0.047 0.0026 1 ++
47 -0.31 -1.2 -0.68 -0.095 0.00016 -0.67 2 0.091 8.4e+03 0.32 0.026 1 ++
48 -0.28 -1.2 -0.67 -0.091 0.00014 -0.68 2 0.086 8.4e+03 2.8 0.26 1 ++
49 -0.22 -1.3 -0.57 -0.096 0.00016 -0.67 2 0.13 8.4e+03 0.78 2.6 1 ++
50 -0.23 -1.3 -0.57 -0.095 0.00016 -0.67 2 0.12 8.4e+03 0.012 26 1 ++
51 -0.22 -1.4 -0.57 -0.095 0.00016 -0.67 2 0.12 8.4e+03 0.00012 2.6e+02 1 ++
52 -0.22 -1.4 -0.57 -0.095 0.00016 -0.67 2 0.12 8.4e+03 2.2e-06 2.6e+02 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 7 unknown parameters [max: 50]
*** Estimate b07everything_000071
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_com lambda_travel_t b_cost mu_existing asc_car Function Relgrad Radius Rho
0 -0.84 -0.93 0.079 1.8 -1 1.6 0.35 9.3e+03 0.11 1 0.53 +
1 -0.84 -0.93 0.079 1.8 -1 1.6 0.35 9.3e+03 0.11 0.5 -0.37 -
2 -0.53 -0.81 0.19 1.5 -0.82 1.5 -0.15 8.7e+03 0.024 5 0.93 ++
3 -0.53 -0.81 0.19 1.5 -0.82 1.5 -0.15 8.7e+03 0.024 2.5 -37 -
4 -0.53 -0.81 0.19 1.5 -0.82 1.5 -0.15 8.7e+03 0.024 1.2 -3.2 -
5 0.059 -1.5 -0.0099 0.23 -0.58 2.5 0.28 8.5e+03 0.0084 1.2 0.61 +
6 -0.17 -1.4 -0.16 0.43 -0.64 1.9 0.16 8.5e+03 0.0067 12 0.95 ++
7 -0.21 -1.3 -0.12 0.47 -0.63 2 0.12 8.5e+03 0.00073 1.2e+02 1 ++
8 -0.21 -1.3 -0.11 0.47 -0.62 2 0.12 8.5e+03 3.3e-05 1.2e+03 1 ++
9 -0.21 -1.3 -0.11 0.47 -0.62 2 0.12 8.5e+03 2.8e-08 1.2e+03 1 ++
Considering neighbor 2/20 for current solution
Attempt 52/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000072
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost_train mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.49 0.73 0.32 0.011 -1 -0.62 -0.92 1.9 0.25 -0.57 -0.21 -0.052 -0.075 -0.96 9e+03 0.17 1 0.66 +
1 -0.49 0.73 0.32 0.011 -1 -0.62 -0.92 1.9 0.25 -0.57 -0.21 -0.052 -0.075 -0.96 9e+03 0.17 0.5 -0.53 -
2 -0.54 0.62 0.082 0.046 -0.6 -0.39 -0.58 2 -0.25 -0.47 -0.039 -0.12 -0.35 -0.49 8.3e+03 0.041 0.5 0.79 +
3 -0.79 0.88 0.21 0.049 -0.74 -0.56 -0.59 2 -0.37 -0.26 -0.06 -0.38 -0.24 -0.68 8.2e+03 0.0056 5 1.1 ++
4 -0.94 1 0.31 0.21 -0.88 -0.63 -0.76 1.4 -0.36 -0.46 -0.062 -0.41 -0.28 -0.77 8.2e+03 0.0086 5 0.56 +
5 -1 1 0.35 0.26 -0.87 -0.63 -0.77 1.5 -0.37 -0.5 -0.066 -0.43 -0.27 -0.77 8.2e+03 0.00064 50 1 ++
6 -0.99 1 0.35 0.25 -0.87 -0.63 -0.77 1.5 -0.37 -0.49 -0.066 -0.42 -0.27 -0.77 8.2e+03 4.1e-05 5e+02 1 ++
7 -0.99 1 0.35 0.25 -0.87 -0.63 -0.77 1.5 -0.37 -0.49 -0.066 -0.42 -0.27 -0.77 8.2e+03 1.1e-07 5e+02 1 ++
Considering neighbor 0/20 for current solution
Considering neighbor 1/20 for current solution
Attempt 53/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000073
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train lambda_travel_t b_cost mu_existing asc_car b_time_car b_time_swissmet Function Relgrad Radius Rho
0 -0.9 -0.79 1.7 -1 1.8 -0.01 -0.56 -0.61 9e+03 0.086 1 0.68 +
1 -0.9 -0.79 1.7 -1 1.8 -0.01 -0.56 -0.61 9e+03 0.086 0.5 -0.3 -
2 -0.43 -0.86 1.2 -0.5 2 -0.36 -0.4 -0.77 8.6e+03 0.052 0.5 0.73 +
3 -0.35 -1.1 0.72 -0.65 2.3 -0.1 -0.7 -0.95 8.4e+03 0.015 5 0.91 ++
4 0.096 -1.7 0.02 -0.55 2.8 0.073 -1 -1.4 8.3e+03 0.017 5 0.67 +
5 0.05 -1.9 0.15 -0.62 2.3 0.077 -1.1 -1.4 8.3e+03 0.0056 50 1.1 ++
6 0.025 -1.9 0.17 -0.62 2.3 0.073 -1.1 -1.3 8.3e+03 5.4e-05 5e+02 1 ++
7 0.025 -1.9 0.17 -0.62 2.3 0.073 -1.1 -1.3 8.3e+03 4.9e-07 5e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 54/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000074
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time lambda_travel_t b_cost_train mu_existing asc_car b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.64 -1 1.4 -0.54 1.9 0.25 0.13 -0.65 1e+04 0.24 1 0.37 +
1 -0.64 -1 1.4 -0.54 1.9 0.25 0.13 -0.65 1e+04 0.24 0.5 -1.2 -
2 -0.27 -0.87 1.1 -0.43 1.8 -0.25 -0.27 -0.45 8.7e+03 0.09 0.5 0.77 +
3 -0.2 -0.88 0.7 -0.93 2.1 -0.32 -0.23 -0.52 8.4e+03 0.015 5 1 ++
4 0.17 -1.4 0.29 -1.2 1.8 -0.12 -0.31 -0.59 8.3e+03 0.0056 50 1 ++
5 0.24 -1.5 0.39 -1.3 1.7 -0.092 -0.35 -0.63 8.3e+03 0.00065 5e+02 0.96 ++
6 0.24 -1.5 0.38 -1.3 1.7 -0.092 -0.35 -0.63 8.3e+03 8.8e-06 5e+03 1 ++
7 0.24 -1.5 0.38 -1.3 1.7 -0.092 -0.35 -0.63 8.3e+03 4.6e-09 5e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 55/100
Considering neighbor 0/20 for current solution
Attempt 56/100
Considering neighbor 0/20 for current solution
Attempt 57/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000075
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.98 0.34 0.28 -0.56 -0.45 -0.72 -0.28 -0.0081 -0.42 8.7e+03 0.039 10 1.1 ++
1 -1.2 0.71 0.67 -0.88 -0.6 -0.83 0.038 -0.11 -0.61 8.5e+03 0.0069 1e+02 1.1 ++
2 -1.4 0.88 0.84 -0.91 -0.64 -0.86 0.053 -0.1 -0.62 8.5e+03 0.0005 1e+03 1 ++
3 -1.4 0.88 0.84 -0.91 -0.64 -0.86 0.053 -0.1 -0.62 8.5e+03 3.4e-06 1e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000076
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.28 -
1 -0.28 -0.12 -0.0055 -0.5 -0.073 -0.11 1.3 0.22 0.065 -0.073 -0.065 -0.0048 -0.18 -0.06 9.3e+03 0.072 0.5 0.77 +
2 -0.3 0.13 0.0064 -0.67 -0.15 -0.61 1.3 -0.21 0.14 -0.11 -0.14 -0.021 -0.32 -0.17 8.8e+03 0.039 5 0.97 ++
3 -0.68 0.69 0.81 -1.2 0.34 -0.66 1.7 -1.3 1.2 -0.55 -0.1 -0.37 -0.88 0.36 8.5e+03 0.04 5 0.89 +
4 -0.68 0.76 0.67 -1.5 0.28 -0.78 1 -1.5 1.2 -0.47 -0.14 -0.39 -0.96 0.34 8.4e+03 0.083 5 0.62 +
5 -0.79 0.77 0.68 -1.7 0.24 -0.76 1 -1.6 1.3 -0.44 -0.09 -0.4 -1.1 0.39 8.4e+03 0.011 50 1.1 ++
6 -0.87 0.91 0.86 -1.8 0.44 -0.8 1 -1.8 1.7 -0.48 -0.1 -0.45 -1.2 0.64 8.4e+03 0.00085 5e+02 1 ++
7 -0.87 0.91 0.86 -1.8 0.44 -0.8 1 -1.8 1.7 -0.48 -0.1 -0.45 -1.2 0.64 8.4e+03 5.4e-06 5e+02 1 ++
Considering neighbor 1/20 for current solution
Attempt 58/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000077
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 -0.98 1 -0.74 -0.62 -0.66 -0.35 -0.49 -0.6 8.5e+03 0.049 10 1.1 ++
1 -0.92 1.3 -1.2 -0.84 -0.73 -0.31 -0.99 -0.38 8.3e+03 0.011 1e+02 1.1 ++
2 -0.86 1.3 -1.3 -1 -0.75 -0.33 -1.1 -0.35 8.3e+03 0.001 1e+03 1.1 ++
3 -0.85 1.3 -1.3 -1 -0.76 -0.33 -1.1 -0.35 8.3e+03 1.7e-05 1e+04 1 ++
4 -0.85 1.3 -1.3 -1 -0.76 -0.33 -1.1 -0.35 8.3e+03 4.9e-09 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 59/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000078
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 0.065 -0.78 -0.089 1.1 -0.27 1.5 -0.34 -0.071 -0.2 -0.14 -0.31 -0.049 9.1e+03 0.079 1 0.61 +
1 -0.71 1.1 -0.83 -0.16 1.1 -0.93 1.5 -0.96 -0.1 -0.42 -0.47 -0.6 -0.052 8.4e+03 0.014 10 0.95 ++
2 -0.71 1.1 -0.83 -0.16 1.1 -0.93 1.5 -0.96 -0.1 -0.42 -0.47 -0.6 -0.052 8.4e+03 0.014 1 -3.6 -
3 -0.36 1.2 -1.6 -0.51 0.081 -0.79 1.4 -1.7 -0.38 0.061 -1 -1.3 -0.12 8.3e+03 0.045 1 0.56 +
4 -0.44 1.4 -2 -0.7 0.25 -0.74 1.1 -1.7 -0.6 0.12 -1.1 -1.5 -0.22 8.2e+03 0.013 10 1.1 ++
5 -0.64 1.6 -2.2 -0.74 0.17 -0.73 1 -1.6 -0.65 0.12 -1.1 -1.5 -0.23 8.2e+03 0.0061 1e+02 1.2 ++
6 -0.66 1.6 -2.2 -0.74 0.18 -0.73 1 -1.6 -0.65 0.13 -1.1 -1.5 -0.23 8.2e+03 0.0026 1e+03 1 ++
7 -0.64 1.6 -2.3 -0.87 0.16 -0.73 1 -1.6 -0.71 0.14 -1 -1.5 -0.27 8.2e+03 0.00011 1e+04 1 ++
8 -0.64 1.6 -2.3 -0.87 0.16 -0.73 1 -1.6 -0.71 0.14 -1 -1.5 -0.27 8.2e+03 8.8e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 60/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000079
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 1.1e+04 0.26 0.5 -0.17 -
1 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 5 1.1 ++
2 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 2.5 1.1 -
3 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 1.2 1.1 -
4 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.62 1.1 -
5 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.31 -4.6 -
6 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.16 -3.1 -
7 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.078 -2.3 -
8 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.039 -2.6 -
9 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.02 -3.3 -
10 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.0098 -4.3 -
11 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.0049 -5.1 -
12 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.0024 -4.4 -
13 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.0012 -2.6 -
14 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.00061 -1.3 -
15 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.00031 -0.2 -
16 -0.5 0.0014 -0.5 -0.5 0.00031 -0.00031 -0.5 1 0.034 -0.5 8.8e+03 2.8 0.00031 0.66 +
17 -0.5 0.0014 -0.5 -0.5 0.00061 -0.00023 -0.5 1 0.034 -0.5 8.8e+03 1.2 0.00031 0.81 +
18 -0.5 0.0014 -0.5 -0.5 0.00092 -0.00026 -0.5 1 0.034 -0.5 8.8e+03 0.15 0.0031 0.99 ++
19 -0.5 0.0019 -0.5 -0.5 0.004 -0.00026 -0.5 1 0.033 -0.5 8.8e+03 0.32 0.031 1 ++
20 -0.51 0.0062 -0.52 -0.51 0.034 -0.00041 -0.5 1 0.032 -0.5 8.7e+03 0.23 0.31 1 ++
21 -0.68 0.31 -0.78 -0.56 0.025 -0.00036 -0.7 1.3 0.038 -0.6 8.4e+03 0.12 3.1 0.98 ++
22 -0.68 0.31 -0.78 -0.56 0.025 -0.00036 -0.7 1.3 0.038 -0.6 8.4e+03 0.12 1.5 -38 -
23 -0.68 0.31 -0.78 -0.56 0.025 -0.00036 -0.7 1.3 0.038 -0.6 8.4e+03 0.12 0.76 -3.7 -
24 -0.58 1.1 -1 -0.68 -0.12 0.00025 -0.79 1.4 -0.17 -0.78 8.3e+03 18 0.76 0.44 +
25 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.76 0.47 +
26 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.38 -4.8 -
27 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.19 -3.2 -
28 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.095 -2.5 -
29 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.048 -2.2 -
30 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.024 -2.2 -
31 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.012 -2.3 -
32 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.006 -2.5 -
33 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.003 -2.7 -
34 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.0015 -2.9 -
35 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.00075 -3 -
36 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.00037 -3.1 -
37 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.00019 -1.5 -
38 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 9.3e-05 -0.49 -
39 -0.38 1.1 -1.7 -0.53 -0.077 3.2e-05 -0.76 1.4 0.15 -1.1 8.2e+03 14 9.3e-05 0.3 +
40 -0.38 1.1 -1.7 -0.53 -0.077 3.2e-05 -0.76 1.4 0.15 -1.1 8.2e+03 14 4.7e-05 -0.37 -
41 -0.38 1.1 -1.7 -0.53 -0.077 7.8e-05 -0.76 1.4 0.15 -1.1 8.2e+03 7.9 4.7e-05 0.61 +
42 -0.38 1.1 -1.7 -0.53 -0.077 6.7e-05 -0.76 1.4 0.15 -1.1 8.2e+03 0.63 0.00047 0.94 ++
43 -0.38 1.1 -1.7 -0.53 -0.077 7e-05 -0.76 1.4 0.15 -1.1 8.2e+03 0.17 0.0047 1 ++
44 -0.38 1.1 -1.7 -0.53 -0.082 9.1e-05 -0.76 1.4 0.15 -1.1 8.2e+03 0.62 0.047 1 ++
45 -0.43 1.1 -1.8 -0.54 -0.11 0.00022 -0.76 1.4 0.13 -1.1 8.2e+03 8.3 0.047 0.78 +
46 -0.47 1.1 -1.8 -0.55 -0.11 0.00021 -0.76 1.4 0.099 -1.1 8.2e+03 0.78 0.47 1 ++
47 -0.73 1.3 -1.6 -0.67 -0.1 0.00018 -0.78 1.1 0.11 -1.3 8.2e+03 3.3 4.7 1 ++
48 -0.83 1.4 -1.6 -0.67 -0.1 0.00019 -0.77 1.1 0.12 -1.3 8.2e+03 0.18 47 1.1 ++
49 -0.89 1.5 -1.7 -0.68 -0.1 0.00019 -0.77 1 0.13 -1.3 8.2e+03 0.0086 4.7e+02 1 ++
50 -0.9 1.5 -1.7 -0.68 -0.1 0.00019 -0.77 1 0.13 -1.3 8.2e+03 0.034 4.7e+03 1 ++
51 -0.9 1.5 -1.7 -0.68 -0.1 0.00019 -0.78 1 0.13 -1.3 8.2e+03 7.4e-05 4.7e+04 1 ++
52 -0.9 1.5 -1.7 -0.68 -0.1 0.00019 -0.78 1 0.13 -1.3 8.2e+03 0.0017 4.7e+05 1 ++
53 -0.9 1.5 -1.7 -0.68 -0.1 0.00019 -0.78 1 0.13 -1.3 8.2e+03 2.1e-07 4.7e+05 1 ++
Considering neighbor 0/20 for current solution
Attempt 61/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000080
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -0.98 -0.8 -0.39 2 -0.82 -0.72 -0.41 -0.54 -0.63 -0.5 9.2e+03 0.1 1 0.62 +
1 -0.98 -0.8 -0.39 2 -0.82 -0.72 -0.41 -0.54 -0.63 -0.5 9.2e+03 0.1 0.5 -0.39 -
2 -0.69 -0.77 -0.52 1.8 -0.79 -0.48 -0.49 -0.23 -0.13 -0.41 8.7e+03 0.025 0.5 0.86 +
3 -0.92 -0.78 -0.58 1.3 -0.83 -0.55 -0.66 -0.33 -0.21 -0.55 8.6e+03 0.0088 5 1.1 ++
4 -0.92 -0.78 -0.58 1.3 -0.83 -0.55 -0.66 -0.33 -0.21 -0.55 8.6e+03 0.0088 2.3 -1e+02 -
5 -0.92 -0.78 -0.58 1.3 -0.83 -0.55 -0.66 -0.33 -0.21 -0.55 8.6e+03 0.0088 1.2 -4.4 -
6 -0.26 -1.7 -1.3 0.18 -0.88 -1.4 -1.1 0.033 -0.67 -1 8.5e+03 0.026 1.2 0.54 +
7 -0.16 -2.2 -1.1 0.2 -0.87 -1.5 -0.35 0.084 -0.96 -0.91 8.4e+03 0.002 12 0.96 ++
8 -0.18 -2.1 -1.1 0.25 -0.88 -1.5 -0.41 0.081 -0.95 -0.91 8.4e+03 3e-05 1.2e+02 1 ++
9 -0.18 -2.1 -1.1 0.25 -0.88 -1.5 -0.41 0.081 -0.95 -0.91 8.4e+03 1.3e-08 1.2e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 62/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000081
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train square_tt_coef cube_tt_coef b_cost_train b_time_swissmet b_cost_swissmet asc_car b_time_car b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.41 -
1 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.5 0.3 +
2 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.25 -7.2 -
3 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.12 -8.3 -
4 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.062 -64 -
5 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.031 -0.014 -
6 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.31 0.9 ++
7 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.16 -3.8 -
8 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.078 -5.5 -
9 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.039 -6.8 -
10 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.02 -4.4 -
11 -0.24 -0.47 -0.028 0.00049 -0.24 0.17 0.21 0.0093 -0.01 -0.039 9.4e+03 0.27 0.2 0.99 ++
12 -0.26 -0.55 0.018 -0.0012 -0.34 0.074 0.014 -0.021 -0.13 -0.09 9.2e+03 2.5 2 0.96 ++
13 -0.26 -0.55 0.018 -0.0012 -0.34 0.074 0.014 -0.021 -0.13 -0.09 9.2e+03 2.5 0.98 -2.6 -
14 -0.26 -0.55 0.018 -0.0012 -0.34 0.074 0.014 -0.021 -0.13 -0.09 9.2e+03 2.5 0.49 -1.1 -
15 -0.26 -0.55 0.018 -0.0012 -0.34 0.074 0.014 -0.021 -0.13 -0.09 9.2e+03 2.5 0.24 0.038 -
16 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.24 0.77 +
17 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.12 -7.3 -
18 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.061 -7.7 -
19 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.031 -8 -
20 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.015 -6.7 -
21 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.0076 -4.2 -
22 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.0038 -2.9 -
23 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.0019 -1.7 -
24 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.00095 -0.55 -
25 -0.26 -0.63 0.1 -0.001 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 3.2 0.00095 0.39 +
26 -0.26 -0.63 0.1 -0.001 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 3.2 0.00048 -0.26 -
27 -0.26 -0.63 0.1 -0.00054 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 2.8 0.00048 0.46 +
28 -0.26 -0.63 0.1 -0.00054 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 2.8 0.00024 -0.37 -
29 -0.26 -0.63 0.1 -0.00078 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 2.2 0.00024 0.4 +
30 -0.26 -0.63 0.1 -0.00063 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 1.7 0.00024 0.49 +
31 -0.26 -0.63 0.1 -0.00071 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 0.6 0.00024 0.85 +
32 -0.26 -0.63 0.1 -0.00069 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 0.081 0.0024 1 ++
33 -0.26 -0.63 0.1 -0.0007 -0.47 -0.11 -0.15 -0.11 -0.37 -0.2 9e+03 0.36 0.024 1 ++
34 -0.27 -0.63 0.1 -0.00068 -0.48 -0.13 -0.17 -0.1 -0.35 -0.19 8.9e+03 0.059 0.24 1 ++
35 -0.28 -0.7 0.29 -0.0015 -0.62 -0.37 -0.31 -0.11 -0.38 -0.2 8.8e+03 0.064 0.24 0.84 +
36 -0.25 -0.64 0.36 -0.0017 -0.85 -0.61 -0.45 -0.25 -0.51 -0.3 8.6e+03 0.023 2.4 0.91 ++
37 -0.25 -0.64 0.36 -0.0017 -0.85 -0.61 -0.45 -0.25 -0.51 -0.3 8.6e+03 0.023 1.2 -75 -
38 -0.25 -0.64 0.36 -0.0017 -0.85 -0.61 -0.45 -0.25 -0.51 -0.3 8.6e+03 0.023 0.6 -1 -
39 -0.34 -0.77 0.055 -0.00054 -1.4 -0.75 -0.64 -0.52 -0.62 -0.47 8.5e+03 1.8 0.6 0.86 +
40 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 6 1.2 ++
41 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 1.9 -2.1e+02 -
42 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 0.94 -32 -
43 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 0.47 -4.8 -
44 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 0.24 -0.35 -
45 -0.16 -1.4 -0.072 -2.1e-05 -1.9 -1.5 -0.74 -0.54 -1.1 -0.61 8.4e+03 9.4 0.24 0.71 +
46 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.24 0.41 +
47 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.12 -4 -
48 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.059 -3.8 -
49 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.029 -3.6 -
50 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.015 -3.6 -
51 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.0074 -3.7 -
52 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.0037 -3.8 -
53 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.0018 -3.9 -
54 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.00092 -2.6 -
55 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.00046 -1.6 -
56 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.00023 -0.78 -
57 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.00012 -0.036 -
58 -0.076 -1.6 -0.074 3.6e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 4.4 0.00012 0.71 +
59 -0.076 -1.6 -0.074 5e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 1.2 0.00012 0.83 +
60 -0.076 -1.6 -0.074 4.7e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 0.023 0.0012 1 ++
61 -0.077 -1.6 -0.073 4.2e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 0.02 0.012 1 ++
62 -0.081 -1.6 -0.069 2.5e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 0.037 0.12 1 ++
63 -0.051 -1.7 -0.091 0.00014 -1.9 -1.8 -0.75 -0.54 -1.4 -0.64 8.4e+03 9.7 1.2 0.92 ++
64 0.37 -2.5 -0.12 0.00024 -1.9 -2.4 -0.8 -0.51 -1.9 -0.64 8.3e+03 31 1.2 0.62 +
65 0.44 -2.6 -0.11 0.00023 -1.9 -2.5 -0.8 -0.51 -2 -0.64 8.3e+03 5.5 1.2 0.83 +
66 0.4 -2.5 -0.11 0.00021 -1.9 -2.4 -0.8 -0.53 -1.9 -0.66 8.3e+03 3 1.2 0.78 +
67 0.4 -2.5 -0.11 0.00022 -1.9 -2.4 -0.8 -0.53 -1.9 -0.65 8.3e+03 0.26 12 1 ++
68 0.4 -2.5 -0.11 0.00022 -1.9 -2.4 -0.8 -0.53 -1.9 -0.65 8.3e+03 0.0035 1.2e+02 1 ++
69 0.4 -2.5 -0.11 0.00022 -1.9 -2.4 -0.8 -0.53 -1.9 -0.65 8.3e+03 4.4e-07 1.2e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 63/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000082
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.18 -
1 -0.28 0.024 -0.5 -0.073 -0.094 1.2 0.22 0.06 -0.052 -0.043 -0.14 -0.05 9.2e+03 0.057 0.5 0.87 +
2 -0.17 0.52 -0.67 -0.25 -0.59 1.2 -0.28 0.22 0.086 -0.54 -0.18 -0.33 9e+03 0.16 5 0.93 ++
3 -0.17 0.52 -0.67 -0.25 -0.59 1.2 -0.28 0.22 0.086 -0.54 -0.18 -0.33 9e+03 0.16 2.5 -8.8 -
4 -0.17 0.52 -0.67 -0.25 -0.59 1.2 -0.28 0.22 0.086 -0.54 -0.18 -0.33 9e+03 0.16 1.2 -1.2 -
5 -0.5 1.3 -1.1 -0.28 -0.63 2.4 -1.2 0.091 -0.4 -0.79 -1.1 -0.21 8.6e+03 0.088 1.2 0.35 +
6 -0.5 1.3 -1.1 -0.28 -0.63 2.4 -1.2 0.091 -0.4 -0.79 -1.1 -0.21 8.6e+03 0.088 0.62 -1.3 -
7 -0.66 0.73 -0.53 0.099 -0.69 2.4 -0.86 0.72 -0.46 -1.1 -0.63 -0.15 8.3e+03 0.1 0.62 0.66 +
8 -0.63 0.83 -0.83 0.25 -0.69 2.1 -1.2 0.98 -0.41 -1.3 -0.87 0.27 8.2e+03 0.039 6.2 1.2 ++
9 -0.63 0.83 -0.83 0.25 -0.69 2.1 -1.2 0.98 -0.41 -1.3 -0.87 0.27 8.2e+03 0.039 0.47 0.058 -
10 -0.59 0.92 -1.1 0.23 -0.7 1.6 -1.4 1 -0.44 -1.3 -0.97 0.23 8.2e+03 0.031 4.7 1.2 ++
11 -0.76 1.2 -1.3 0.38 -0.75 1.2 -1.6 1.5 -0.49 -1.1 -1.1 0.57 8.2e+03 0.028 47 1.2 ++
12 -0.9 1.4 -1.5 0.36 -0.75 1.1 -1.8 1.6 -0.49 -1 -1.2 0.63 8.2e+03 0.012 4.7e+02 1.3 ++
13 -0.93 1.4 -1.5 0.35 -0.75 1 -1.7 1.6 -0.48 -1 -1.2 0.63 8.2e+03 0.0031 4.7e+03 1.1 ++
14 -0.93 1.5 -1.6 0.35 -0.75 1 -1.7 1.6 -0.48 -1 -1.2 0.63 8.2e+03 0.0026 4.7e+04 1 ++
15 -0.97 1.6 -1.6 0.33 -0.75 1 -1.8 1.6 -0.48 -1 -1.2 0.64 8.2e+03 7.7e-05 4.7e+05 1 ++
16 -0.97 1.6 -1.6 0.33 -0.75 1 -1.8 1.6 -0.48 -1 -1.2 0.64 8.2e+03 3.1e-08 4.7e+05 1 ++
Considering neighbor 0/20 for current solution
Attempt 64/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000083
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -1 0.98 0.16 0.076 -0.83 0.32 -0.65 -0.3 -0.39 0.025 -0.11 8.5e+03 0.041 10 1.1 ++
1 -1.3 1.3 0.4 0.45 -1.1 0.0035 -0.69 0.0048 -1.1 -0.028 -0.43 8.3e+03 0.0098 1e+02 1.1 ++
2 -1.5 1.4 0.54 0.62 -1.2 -0.16 -0.7 0.029 -1.2 -0.03 -0.46 8.3e+03 0.00076 1e+03 1 ++
3 -1.5 1.4 0.56 0.64 -1.2 -0.17 -0.7 0.03 -1.2 -0.031 -0.46 8.3e+03 6.1e-06 1e+04 1 ++
4 -1.5 1.4 0.56 0.64 -1.2 -0.17 -0.7 0.03 -1.2 -0.031 -0.46 8.3e+03 4.6e-10 1e+04 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000084
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2.3 -
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.41 -
2 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 2.5 1.1 ++
3 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 1.2 -6.2 -
4 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.62 -4.8 -
5 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.31 -1.6 -
6 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.16 -0.23 -
7 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.16 0.17 +
8 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.078 -0.79 -
9 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.039 -0.7 -
10 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.02 -0.64 -
11 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.0098 -0.58 -
12 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.0049 -0.11 -
13 -0.35 0.026 -0.17 -0.012 -0.41 -0.085 0.12 0.0012 -0.35 0.22 0.03 -0.055 -0.016 -0.0087 0.01 9.2e+03 5.2 0.0049 0.32 +
14 -0.35 0.026 -0.17 -0.012 -0.41 -0.085 0.12 0.0012 -0.35 0.22 0.03 -0.055 -0.016 -0.0087 0.01 9.2e+03 5.2 0.0024 -0.49 -
15 -0.35 0.028 -0.16 -0.015 -0.41 -0.083 0.12 -0.0013 -0.35 0.22 0.032 -0.057 -0.018 -0.011 0.012 9.1e+03 4.1 0.0024 0.66 +
16 -0.35 0.029 -0.16 -0.015 -0.42 -0.083 0.12 -0.0008 -0.36 0.22 0.033 -0.058 -0.019 -0.011 0.013 9.1e+03 1.5 0.024 1.4 ++
17 -0.36 0.037 -0.16 -0.015 -0.44 -0.086 0.13 -0.0008 -0.37 0.19 0.037 -0.065 -0.02 -0.012 0.017 9.1e+03 0.89 0.24 1 ++
18 -0.43 0.12 -0.12 -0.014 -0.63 -0.11 0.25 -0.0013 -0.49 -0.05 0.071 -0.14 -0.041 -0.018 0.053 8.8e+03 1.1 2.4 0.94 ++
19 -0.43 0.12 -0.12 -0.014 -0.63 -0.11 0.25 -0.0013 -0.49 -0.05 0.071 -0.14 -0.041 -0.018 0.053 8.8e+03 1.1 1.2 -60 -
20 -0.43 0.12 -0.12 -0.014 -0.63 -0.11 0.25 -0.0013 -0.49 -0.05 0.071 -0.14 -0.041 -0.018 0.053 8.8e+03 1.1 0.61 -8.1 -
21 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.61 0.88 +
22 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.31 -5.4 -
23 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.15 -4.2 -
24 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.076 -4 -
25 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.038 -4.2 -
26 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.019 -4.4 -
27 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0095 -3.5 -
28 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0048 -2.5 -
29 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0024 -2 -
30 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0012 -1.5 -
31 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0006 -0.88 -
32 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0003 -0.31 -
33 -0.56 0.67 0.23 0.0016 -1 -0.1 0.026 -0.00053 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 6.2 0.0003 0.14 +
34 -0.56 0.67 0.23 0.0016 -1 -0.1 0.026 -0.00053 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 6.2 0.00015 -0.18 -
35 -0.56 0.67 0.23 0.0018 -1 -0.1 0.026 -0.00038 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 2.9 0.0015 0.96 ++
36 -0.56 0.67 0.23 0.0018 -1 -0.1 0.027 -0.00037 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 0.98 0.015 0.98 ++
37 -0.57 0.67 0.22 0.0018 -1 -0.1 0.042 -0.00044 -1 -0.65 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 0.05 0.15 1 ++
38 -0.71 0.73 0.18 0.01 -1.2 -0.14 -0.027 -0.00015 -1.1 -0.57 -0.2 -0.56 -0.25 -0.073 -0.18 8.3e+03 0.2 1.5 1.1 ++
39 -0.71 0.73 0.18 0.01 -1.2 -0.14 -0.027 -0.00015 -1.1 -0.57 -0.2 -0.56 -0.25 -0.073 -0.18 8.3e+03 0.2 0.65 -11 -
40 -0.79 1.1 0.43 0.069 -1.8 -0.37 -0.12 0.00024 -1.2 -0.84 -0.28 -0.74 -0.016 -0.14 -0.41 8.2e+03 32 0.65 0.63 +
41 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.65 0.62 +
42 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.33 -3 -
43 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.16 -1.9 -
44 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.082 -1.4 -
45 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.041 -1.2 -
46 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.02 -1.1 -
47 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.01 -1.2 -
48 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.0051 -1.4 -
49 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.0026 -1.6 -
50 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.0013 -1.8 -
51 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.00064 -1.9 -
52 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.00032 -2 -
53 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.00016 -2 -
54 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 8e-05 -1.8 -
55 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 4e-05 -0.57 -
56 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00012 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 28 4e-05 0.29 +
57 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00012 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 28 2e-05 -0.12 -
58 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00014 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 14 2e-05 0.57 +
59 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00014 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 1.8 0.0002 0.91 ++
60 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00014 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 0.16 0.002 1 ++
61 -0.76 1.2 0.48 0.3 -2.3 -1 -0.096 0.00015 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 0.95 0.02 1 ++
62 -0.77 1.2 0.47 0.3 -2.3 -1 -0.11 0.00022 -1.1 -0.75 -0.15 -0.92 -0.064 -0.28 -0.29 8.1e+03 8 0.02 0.81 +
63 -0.79 1.2 0.46 0.3 -2.3 -1 -0.11 0.00022 -1.1 -0.75 -0.14 -0.92 -0.067 -0.28 -0.29 8.1e+03 0.25 0.2 1 ++
64 -0.93 1.2 0.56 0.5 -2.1 -1.2 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.08 -0.44 -0.35 8.1e+03 0.73 2 1 ++
65 -0.93 1.2 0.55 0.53 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.082 -0.5 -0.36 8.1e+03 0.04 20 1 ++
66 -0.93 1.2 0.55 0.52 -2.1 -1.2 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.083 -0.5 -0.36 8.1e+03 6.1e-05 2e+02 1 ++
67 -0.93 1.2 0.55 0.52 -2.1 -1.2 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.083 -0.51 -0.36 8.1e+03 0.0045 2e+03 1 ++
68 -0.93 1.2 0.55 0.52 -2.1 -1.2 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.083 -0.51 -0.36 8.1e+03 2e-06 2e+03 1 ++
Considering neighbor 1/20 for current solution
Attempt 65/100
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000085
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.26 0.5 0 -
1 1.1e+04 0.26 0.25 -0.38 -
2 9.5e+03 2.1 2.5 1 ++
3 9.5e+03 2.1 1.2 1 -
4 9.5e+03 2.1 0.62 -4.2 -
5 9.5e+03 2.1 0.31 -2.6 -
6 9.5e+03 2.1 0.16 -0.34 -
7 9.4e+03 11 0.16 0.2 +
8 9.4e+03 11 0.078 -0.8 -
9 9.4e+03 11 0.039 -0.7 -
10 9.4e+03 11 0.02 -0.64 -
11 9.4e+03 11 0.0098 -0.59 -
12 9.4e+03 11 0.0049 -0.11 -
13 9.2e+03 5.2 0.0049 0.32 +
14 9.2e+03 5.2 0.0024 -0.5 -
15 9.1e+03 4.1 0.0024 0.65 +
16 9.1e+03 2 0.024 1.4 ++
17 9e+03 2.7 0.24 0.97 ++
18 8.8e+03 2.5 2.4 0.96 ++
19 8.8e+03 2.5 1.2 0.96 -
20 8.8e+03 2.5 0.61 -14 -
21 8.4e+03 12 6.1 0.92 ++
22 8.4e+03 12 3.1 0.92 -
23 8.4e+03 12 1.5 0.92 -
24 8.4e+03 12 0.76 -53 -
25 8.4e+03 12 0.38 -11 -
26 8.4e+03 12 0.19 -3.6 -
27 8.4e+03 12 0.095 -2 -
28 8.4e+03 12 0.048 -1.2 -
29 8.4e+03 12 0.024 -1.2 -
30 8.4e+03 12 0.012 -1.3 -
31 8.4e+03 12 0.006 -1.5 -
32 8.4e+03 12 0.003 -1.6 -
33 8.4e+03 12 0.0015 -1.8 -
34 8.4e+03 12 0.00075 -1.8 -
35 8.4e+03 12 0.00037 -0.62 -
36 8.4e+03 12 0.00019 -0.16 -
37 8.4e+03 5.4 0.00019 0.18 +
38 8.4e+03 5.4 9.3e-05 -0.27 -
39 8.4e+03 0.66 9.3e-05 0.85 +
40 8.4e+03 0.039 0.00093 1 ++
41 8.4e+03 0.17 0.0093 1 ++
42 8.3e+03 0.029 0.093 1 ++
43 8.3e+03 0.091 0.93 1 ++
44 8.3e+03 0.091 0.47 -14 -
45 8.3e+03 0.091 0.23 -0.55 -
46 8.2e+03 2.3 2.3 0.95 ++
47 8.1e+03 11 23 0.91 ++
48 8.1e+03 11 23 0.74 +
49 8.1e+03 2 2.3e+02 0.99 ++
50 8.1e+03 0.029 2.3e+03 1 ++
51 8.1e+03 0.13 2.3e+04 1 ++
52 8.1e+03 0.0003 2.3e+05 1 ++
53 8.1e+03 7.7e-07 2.3e+05 1 ++
Considering neighbor 0/20 for current solution
Attempt 66/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000086
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_time_car b_cost_car b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.48 -
1 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.5 0.31 +
2 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.25 0.31 -
3 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.12 0.31 -
4 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.062 -86 -
5 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.031 -0.54 -
6 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.31 0.92 ++
7 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.16 0.92 -
8 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.078 0.92 -
9 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.039 -7.6 -
10 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.02 -24 -
11 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.0098 -0.083 -
12 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.098 0.97 ++
13 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.049 -18 -
14 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.024 -19 -
15 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.012 -14 -
16 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.0061 -4 -
17 -0.22 0.047 -0.47 -0.042 -0.00037 -0.26 1.2 -0.028 -0.069 -0.0061 -0.054 0.16 0.2 9.3e+03 0.061 0.061 0.95 ++
18 -0.22 0.072 -0.48 -0.04 -1.1e-05 -0.28 1.2 -0.027 -0.09 -0.021 -0.059 0.12 0.13 9.2e+03 0.041 0.61 1 ++
19 -0.23 0.43 -0.65 0.097 -0.0019 -0.57 1.7 -0.2 -0.39 -0.53 -0.33 -0.26 -0.48 8.6e+03 16 0.61 0.65 +
20 -0.23 0.43 -0.65 0.097 -0.0019 -0.57 1.7 -0.2 -0.39 -0.53 -0.33 -0.26 -0.48 8.6e+03 16 0.31 -0.99 -
21 -0.23 0.43 -0.65 0.097 -0.0019 -0.57 1.7 -0.2 -0.39 -0.53 -0.33 -0.26 -0.48 8.6e+03 16 0.15 -0.5 -
22 -0.23 0.43 -0.65 0.097 -0.0019 -0.57 1.7 -0.2 -0.39 -0.53 -0.33 -0.26 -0.48 8.6e+03 16 0.076 -0.15 -
23 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.076 0.12 +
24 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.038 0.12 -
25 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.019 0.12 -
26 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.0095 0.12 -
27 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.0048 -1.9 -
28 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.0024 -0.7 -
29 -0.25 0.45 -0.73 0.023 -0.00051 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.4 0.0024 0.86 +
30 -0.25 0.45 -0.73 0.023 -0.00051 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.4 0.0012 -1.1 -
31 -0.25 0.45 -0.73 0.023 -0.00051 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.4 0.0006 -1.1 -
32 -0.25 0.45 -0.73 0.023 -0.00051 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.4 0.0003 -0.7 -
33 -0.25 0.45 -0.73 0.024 -0.00022 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.8 0.0003 0.18 +
34 -0.25 0.45 -0.73 0.024 -0.00022 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.8 0.00015 -0.094 -
35 -0.25 0.45 -0.73 0.024 -0.00037 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 3.1 0.00015 0.58 +
36 -0.25 0.45 -0.73 0.024 -0.00033 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 0.9 0.00015 0.84 +
37 -0.25 0.45 -0.73 0.024 -0.00034 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 0.043 0.0015 1 ++
38 -0.25 0.45 -0.73 0.026 -0.00035 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 0.2 0.015 1 ++
39 -0.26 0.46 -0.73 0.04 -0.00041 -0.61 1.7 -0.15 -0.41 -0.53 -0.29 -0.34 -0.5 8.4e+03 0.027 0.15 1 ++
40 -0.25 0.52 -0.73 0.14 -0.00082 -0.64 1.8 -0.16 -0.43 -0.58 -0.31 -0.49 -0.5 8.3e+03 0.42 1.5 1 ++
41 -0.25 0.52 -0.73 0.14 -0.00082 -0.64 1.8 -0.16 -0.43 -0.58 -0.31 -0.49 -0.5 8.3e+03 0.42 0.75 -1.1e+02 -
42 -0.25 0.52 -0.73 0.14 -0.00082 -0.64 1.8 -0.16 -0.43 -0.58 -0.31 -0.49 -0.5 8.3e+03 0.42 0.37 -14 -
43 -0.4 0.7 -0.85 0.037 -0.00039 -0.74 2 -0.28 -0.53 -0.7 -0.44 -0.86 -0.49 8.2e+03 0.58 3.7 1.1 ++
44 -0.4 0.7 -0.85 0.037 -0.00039 -0.74 2 -0.28 -0.53 -0.7 -0.44 -0.86 -0.49 8.2e+03 0.58 1.9 1.1 -
45 -0.4 0.7 -0.85 0.037 -0.00039 -0.74 2 -0.28 -0.53 -0.7 -0.44 -0.86 -0.49 8.2e+03 0.58 0.93 -1.2e+02 -
46 -0.4 0.7 -0.85 0.037 -0.00039 -0.74 2 -0.28 -0.53 -0.7 -0.44 -0.86 -0.49 8.2e+03 0.58 0.47 -6.9 -
47 -0.57 0.75 -1.3 -0.11 0.0002 -0.55 2 -0.42 -0.47 -1 -0.54 -1.3 -0.58 8.2e+03 16 0.47 0.59 +
48 -0.41 0.91 -1.7 -0.09 0.00015 -0.56 2.1 -0.46 -0.4 -1.3 -0.51 -1.8 -0.54 8.1e+03 16 4.7 0.9 ++
49 -0.41 0.91 -1.7 -0.09 0.00015 -0.56 2.1 -0.46 -0.4 -1.3 -0.51 -1.8 -0.54 8.1e+03 16 0.29 -0.11 -
50 -0.32 0.88 -2 -0.11 0.00023 -0.65 1.9 -0.51 -0.22 -1.5 -0.45 -2.1 -0.58 8.1e+03 21 0.29 0.57 +
51 -0.3 0.98 -2.1 -0.11 0.00021 -0.66 1.8 -0.48 -0.34 -1.6 -0.52 -2.1 -0.62 8.1e+03 0.9 2.9 1 ++
52 -0.3 0.98 -2.1 -0.11 0.00021 -0.68 1.8 -0.46 -0.38 -1.6 -0.53 -2.2 -0.63 8.1e+03 0.022 29 1 ++
53 -0.3 0.98 -2.1 -0.11 0.00021 -0.68 1.8 -0.46 -0.38 -1.6 -0.53 -2.2 -0.63 8.1e+03 0.00014 2.9e+02 1 ++
54 -0.3 0.98 -2.1 -0.11 0.00021 -0.68 1.8 -0.46 -0.38 -1.6 -0.53 -2.2 -0.63 8.1e+03 0.00074 2.9e+03 1 ++
55 -0.3 0.98 -2.1 -0.11 0.00021 -0.68 1.8 -0.46 -0.38 -1.6 -0.53 -2.2 -0.63 8.1e+03 1.6e-06 2.9e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 67/100
Biogeme parameters read from biogeme.toml.
Model with 18 unknown parameters [max: 50]
*** Estimate b07everything_000087
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.38 -
1 9.9e+03 1.5 0.5 0.35 +
2 9.9e+03 1.5 0.25 0.35 -
3 9.9e+03 1.5 0.12 0.35 -
4 9.9e+03 1.5 0.062 0.35 -
5 9.9e+03 1.5 0.031 -1.9 -
6 9.4e+03 0.78 0.31 0.94 ++
7 9.4e+03 0.78 0.16 0.94 -
8 9.4e+03 0.78 0.078 -6 -
9 9.4e+03 0.78 0.039 -8.8 -
10 9.4e+03 0.78 0.02 -12 -
11 9.4e+03 0.78 0.0098 -15 -
12 9.4e+03 0.78 0.0049 -1.8 -
13 9.3e+03 0.42 0.049 0.98 ++
14 9.3e+03 6.1 0.049 0.51 +
15 9.1e+03 0.93 0.049 0.76 +
16 9.1e+03 0.93 0.024 -1.6 -
17 9.1e+03 0.93 0.012 -2.2 -
18 9.1e+03 0.93 0.0061 -3.2 -
19 9.1e+03 0.93 0.0031 -4.2 -
20 9.1e+03 0.93 0.0015 -3.5 -
21 9.1e+03 2.5 0.0015 0.21 +
22 9.1e+03 0.78 0.015 1.1 ++
23 9.1e+03 0.077 0.15 1 ++
24 8.9e+03 0.82 1.5 0.98 ++
25 8.9e+03 0.82 0.76 -2.5 -
26 8.9e+03 0.82 0.38 -0.9 -
27 8.8e+03 6.7 0.38 0.25 +
28 8.5e+03 0.82 0.38 0.51 +
29 8.4e+03 4.1 0.38 0.58 +
30 8.4e+03 4.1 0.19 0.58 -
31 8.4e+03 4.1 0.095 0.58 -
32 8.4e+03 4.1 0.048 0.58 -
33 8.4e+03 4.1 0.024 -4.7 -
34 8.4e+03 4.1 0.012 -3.1 -
35 8.4e+03 4.1 0.006 -2.1 -
36 8.4e+03 4.1 0.003 -0.98 -
37 8.3e+03 5.6 0.003 0.44 +
38 8.3e+03 1.7 0.03 1.2 ++
39 8.3e+03 2.8 0.3 0.91 ++
40 8.2e+03 4.9 0.3 0.79 +
41 8.2e+03 9 0.3 0.39 +
42 8.2e+03 9 0.15 -5.2 -
43 8.2e+03 9 0.075 -4.5 -
44 8.2e+03 9 0.037 -4.4 -
45 8.2e+03 9 0.019 -4.4 -
46 8.2e+03 9 0.0093 -4.7 -
47 8.2e+03 9 0.0047 -4.9 -
48 8.2e+03 9 0.0023 -4.4 -
49 8.2e+03 9 0.0012 -2.6 -
50 8.2e+03 9 0.00058 -1.4 -
51 8.2e+03 9 0.00029 -0.12 -
52 8.2e+03 1.7 0.00029 0.9 +
53 8.2e+03 0.042 0.0029 0.99 ++
54 8.2e+03 0.034 0.029 1 ++
55 8.2e+03 0.28 0.29 1 ++
56 8.1e+03 0.23 2.9 1.1 ++
57 8.1e+03 0.074 29 1 ++
58 8.1e+03 0.13 2.9e+02 1 ++
59 8.1e+03 2.9 2.9e+03 0.91 ++
60 8.1e+03 0.23 2.9e+04 1 ++
61 8.1e+03 0.0024 2.9e+05 1 ++
62 8.1e+03 3.1e-07 2.9e+05 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000088
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.83 0.045 -1 -0.12 -0.2 1.4 -0.029 -0.098 9e+03 0.073 1 0.67 +
1 -0.54 1 -1.1 -0.14 -0.97 1.5 -0.17 -0.48 8.4e+03 0.015 1 0.87 +
2 -0.66 1.1 -1 -0.25 -0.67 1.5 -0.088 -1.3 8.3e+03 0.0018 10 0.99 ++
3 -0.83 1.3 -1.1 -0.22 -0.7 1.2 -0.037 -1.3 8.3e+03 0.0053 10 0.56 +
4 -0.86 1.3 -1.1 -0.22 -0.7 1.2 -0.038 -1.3 8.3e+03 5.6e-05 1e+02 1 ++
5 -0.86 1.3 -1.1 -0.22 -0.7 1.2 -0.038 -1.3 8.3e+03 2.6e-06 1e+02 1 ++
Considering neighbor 1/20 for current solution
Attempt 68/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000089
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.41 -
1 -0.3 -0.11 -0.006 -0.5 -0.24 -0.16 1.4 0.24 0.11 -0.13 -0.1 -0.0067 -0.3 -0.18 9.6e+03 0.17 0.5 0.47 +
2 -0.28 0.12 0.0051 -0.55 -0.31 -0.6 1.6 -0.26 -0.22 -0.13 -0.15 -0.022 -0.29 -0.097 8.8e+03 0.086 0.5 0.78 +
3 -0.42 0.41 0.058 -0.86 -0.48 -0.72 1.6 -0.76 -0.39 -0.28 -0.19 -0.063 -0.52 -0.48 8.5e+03 0.013 5 1.1 ++
4 -0.69 0.57 0.34 -1.2 -0.77 -0.82 1 -1.2 -0.73 -0.66 -0.11 -0.23 -0.64 -0.64 8.5e+03 0.049 5 0.77 +
5 -0.74 0.59 0.35 -1.3 -0.75 -0.84 1 -1.2 -0.73 -0.62 -0.1 -0.24 -0.62 -0.67 8.4e+03 0.0053 50 1 ++
6 -0.91 0.84 0.77 -1.3 -0.8 -0.86 1 -1.1 -0.87 -0.56 -0.1 -0.54 -0.58 -0.77 8.4e+03 0.001 5e+02 1 ++
7 -0.92 0.86 0.77 -1.3 -0.8 -0.86 1 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 8.7e-06 5e+03 1 ++
8 -0.92 0.86 0.77 -1.3 -0.8 -0.86 1 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 8e-09 5e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 69/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000090
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -0.54 -
1 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 5 1.1 ++
2 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 2.5 -11 -
3 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 1.2 -8.9 -
4 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.62 -7.4 -
5 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.31 -3.2 -
6 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.16 -1.7 -
7 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.078 -1.5 -
8 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.039 -1.9 -
9 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.02 -2.5 -
10 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0098 -3.3 -
11 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0049 -4 -
12 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0024 -4.9 -
13 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0012 -2.3 -
14 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.00061 -1.2 -
15 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.00031 -0.22 -
16 -0.5 -0.00028 -0.5 -0.02 -0.5 0.00031 -0.00031 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 2.9 0.00031 0.64 +
17 -0.5 -0.0002 -0.5 -0.02 -0.5 0.00061 -0.00023 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 1.4 0.00031 0.77 +
18 -0.5 -0.00012 -0.5 -0.02 -0.5 0.00092 -0.00026 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 0.14 0.0031 0.99 ++
19 -0.5 0.0007 -0.5 -0.02 -0.5 0.004 -0.00026 -0.14 0.026 -0.078 -0.022 -0.0067 9.2e+03 0.19 0.031 1 ++
20 -0.51 0.0091 -0.49 -0.02 -0.53 0.034 -0.0004 -0.15 0.018 -0.084 -0.03 -0.0071 9.1e+03 0.28 0.31 1 ++
21 -0.56 0.23 -0.32 -0.02 -0.83 0.24 -0.0013 -0.44 0.01 -0.19 -0.1 -0.016 8.8e+03 2.3 0.31 0.75 +
22 -0.64 0.53 -0.096 -0.015 -0.94 0.038 -0.00038 -0.69 0.092 -0.32 -0.13 -0.029 8.5e+03 7.2 0.31 0.82 +
23 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 3.1 1 ++
24 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 1.5 -88 -
25 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 0.76 -13 -
26 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 0.38 -1.3 -
27 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.38 0.11 +
28 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.19 -2.5 -
29 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.095 -1.9 -
30 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.048 -1.5 -
31 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.024 -1.1 -
32 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.012 -1.2 -
33 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.006 -1.6 -
34 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.003 -2 -
35 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.0015 -2.3 -
36 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.00075 -2.6 -
37 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.00037 -2.7 -
38 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.00019 -0.28 -
39 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00044 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 3.2 0.00019 0.89 +
40 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00041 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 0.43 0.0019 0.96 ++
41 -1.1 1.2 0.22 0.019 -1.6 -0.13 0.0004 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 0.26 0.019 1 ++
42 -1.1 1.2 0.22 0.019 -1.6 -0.11 0.00024 -0.71 0.092 -0.6 -0.14 -0.082 8.3e+03 3.6 0.19 0.99 ++
43 -1.1 1.3 0.27 0.04 -1.8 -0.089 0.00011 -0.72 0.13 -0.66 -0.098 -0.099 8.2e+03 7.2 1.9 0.93 ++
44 -1.2 1.4 0.49 0.54 -2.1 -0.12 0.00025 -0.72 0.2 -1.2 -0.059 -0.4 8.2e+03 3.4 1.9 0.88 +
45 -1.3 1.4 0.55 0.59 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.062 -0.46 8.2e+03 4.3 19 1 ++
46 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.48 8.2e+03 0.27 1.9e+02 1 ++
47 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 0.0022 1.9e+03 1 ++
48 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 0.00016 1.9e+04 1 ++
49 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 0.00045 1.9e+05 1 ++
50 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 6e-07 1.9e+05 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000091
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -1 0.97 0.12 0.035 -0.55 -0.41 -0.66 -0.29 -0.4 -0.0026 -0.12 8.5e+03 0.042 10 1.1 ++
1 -1.3 1.3 0.35 0.36 -0.83 -0.56 -0.75 0.02 -1 -0.057 -0.49 8.2e+03 0.01 1e+02 1.1 ++
2 -1.5 1.3 0.5 0.54 -0.87 -0.6 -0.78 0.034 -1.2 -0.056 -0.54 8.2e+03 0.00076 1e+03 1 ++
3 -1.5 1.4 0.52 0.56 -0.87 -0.6 -0.78 0.035 -1.2 -0.056 -0.54 8.2e+03 6.2e-06 1e+04 1 ++
4 -1.5 1.4 0.52 0.56 -0.87 -0.6 -0.78 0.035 -1.2 -0.056 -0.54 8.2e+03 4.8e-10 1e+04 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000092
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time lambda_travel_t b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.59 -0.068 -0.011 -1 1.4 -0.49 -0.29 -0.29 -0.018 9e+03 0.07 1 0.89 +
1 -0.97 0.93 0.12 -1.8 0.41 -0.74 0.26 -0.057 -0.14 8.5e+03 0.0055 10 0.96 ++
2 -1.2 0.96 1.2 -1.6 0.5 -0.78 0.19 -0.1 -0.51 8.5e+03 0.0014 10 0.88 +
3 -1.2 0.97 0.96 -1.6 0.51 -0.78 0.19 -0.099 -0.57 8.5e+03 5.6e-05 1e+02 1 ++
4 -1.2 0.97 0.96 -1.6 0.51 -0.78 0.19 -0.099 -0.57 8.5e+03 1.7e-07 1e+02 1 ++
Considering neighbor 2/20 for current solution
Attempt 70/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000093
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car b_time_swissmet b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho
0 -0.77 0.24 -0.58 -0.2 1.5 -0.59 2 0.14 -0.32 -0.43 -0.31 -0.097 -0.63 -0.37 -0.59 9.3e+03 0.21 1 0.58 +
1 -0.77 0.24 -0.58 -0.2 1.5 -0.59 2 0.14 -0.32 -0.43 -0.31 -0.097 -0.63 -0.37 -0.59 9.3e+03 0.21 0.5 -0.83 -
2 -0.28 0.53 -0.48 -0.21 1.2 -0.41 2.3 -0.36 -0.44 -0.26 -0.27 -0.44 -0.64 -0.4 -0.52 8.8e+03 0.18 0.5 0.38 +
3 -0.59 0.55 -0.55 -0.22 1 -0.4 2.8 -0.084 -0.38 -0.43 -0.5 -0.37 -0.7 -0.43 -0.56 8.3e+03 0.05 0.5 0.76 +
4 -0.4 0.76 -0.94 -0.49 0.52 -0.41 2.8 -0.14 -0.13 -0.54 -0.72 -0.45 -0.99 -0.53 -0.6 8.1e+03 0.02 5 1.1 ++
5 -0.3 1 -1.5 -0.58 0.22 -0.6 1.6 0.032 -0.23 -0.9 -0.83 -0.59 -1.4 -0.25 -0.7 8.1e+03 0.026 5 0.66 +
6 -0.3 1.1 -1.6 -0.64 0.21 -0.65 1.8 0.072 -0.34 -0.92 -0.78 -0.64 -1.4 -0.26 -0.7 8.1e+03 0.0021 50 1 ++
7 -0.29 1.1 -1.7 -0.69 0.16 -0.69 1.7 0.081 -0.36 -0.95 -0.8 -0.65 -1.5 -0.25 -0.71 8.1e+03 0.00027 5e+02 1 ++
8 -0.29 1.1 -1.7 -0.69 0.16 -0.69 1.7 0.081 -0.36 -0.95 -0.8 -0.65 -1.5 -0.25 -0.71 8.1e+03 2.2e-06 5e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 71/100
Considering neighbor 0/20 for current solution
Attempt 72/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000094
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2.7 -
1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.39 -
2 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 2.5 1 ++
3 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 1.2 1 -
4 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 0.62 1 -
5 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 0.31 -1.7 -
6 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 0.16 -0.12 -
7 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.16 0.3 +
8 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.078 -0.51 -
9 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.039 -0.42 -
10 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.02 -0.36 -
11 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.0098 -0.34 -
12 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.0049 -0.32 -
13 -0.32 0.042 -0.24 -0.01 -0.4 0.11 0.0018 -0.35 1.3 0.045 -0.081 -0.023 -0.0096 0.02 0.17 9.1e+03 5.3 0.0049 0.17 +
14 -0.32 0.042 -0.24 -0.01 -0.4 0.11 0.0018 -0.35 1.3 0.045 -0.081 -0.023 -0.0096 0.02 0.17 9.1e+03 5.3 0.0024 -0.18 -
15 -0.32 0.044 -0.24 -0.0097 -0.4 0.11 -0.00066 -0.35 1.3 0.046 -0.084 -0.026 -0.012 0.021 0.17 9e+03 2.7 0.024 0.99 ++
16 -0.32 0.055 -0.23 -0.0095 -0.42 0.12 -0.00076 -0.36 1.3 0.045 -0.093 -0.032 -0.013 0.021 0.14 8.9e+03 0.55 0.24 1 ++
17 -0.3 0.17 -0.12 -0.0078 -0.57 0.22 -0.0011 -0.44 1.4 0.036 -0.18 -0.097 -0.02 0.015 -0.1 8.6e+03 0.52 2.4 0.97 ++
18 -0.3 0.17 -0.12 -0.0078 -0.57 0.22 -0.0011 -0.44 1.4 0.036 -0.18 -0.097 -0.02 0.015 -0.1 8.6e+03 0.52 1.2 0.97 -
19 -0.3 0.17 -0.12 -0.0078 -0.57 0.22 -0.0011 -0.44 1.4 0.036 -0.18 -0.097 -0.02 0.015 -0.1 8.6e+03 0.52 0.61 -33 -
20 -0.43 0.72 0.27 0.013 -0.93 -0.11 0.0002 -0.93 2 -0.17 -0.58 -0.31 -0.077 -0.18 -0.64 8.5e+03 7.3 0.61 0.3 +
21 -0.47 0.59 0.16 0.029 -1.5 -0.034 -0.00011 -0.63 1.9 -0.18 -0.48 -0.051 -0.11 -0.31 -0.68 8.2e+03 7.8 0.61 0.68 +
22 -0.47 0.59 0.16 0.029 -1.5 -0.034 -0.00011 -0.63 1.9 -0.18 -0.48 -0.051 -0.11 -0.31 -0.68 8.2e+03 7.8 0.31 -5.7 -
23 -0.47 0.59 0.16 0.029 -1.5 -0.034 -0.00011 -0.63 1.9 -0.18 -0.48 -0.051 -0.11 -0.31 -0.68 8.2e+03 7.8 0.15 -2.8 -
24 -0.47 0.59 0.16 0.029 -1.5 -0.034 -0.00011 -0.63 1.9 -0.18 -0.48 -0.051 -0.11 -0.31 -0.68 8.2e+03 7.8 0.076 -0.71 -
25 -0.49 0.6 0.16 0.03 -1.6 -0.11 0.00021 -0.66 2 -0.17 -0.48 -0.05 -0.11 -0.3 -0.65 8.1e+03 19 0.076 0.65 +
26 -0.49 0.67 0.23 0.039 -1.6 -0.1 0.00017 -0.72 2 -0.15 -0.48 -0.06 -0.12 -0.26 -0.59 8.1e+03 0.71 0.76 1 ++
27 -0.6 0.92 0.34 0.19 -2 -0.11 0.00019 -0.81 1.5 -0.16 -0.45 -0.057 -0.31 -0.27 -0.68 8.1e+03 1 0.76 0.87 +
28 -0.59 0.9 0.35 0.22 -2 -0.11 0.0002 -0.79 1.6 -0.17 -0.46 -0.063 -0.36 -0.24 -0.67 8.1e+03 0.27 7.6 1 ++
29 -0.59 0.9 0.35 0.22 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.37 -0.24 -0.66 8.1e+03 0.0069 76 1 ++
30 -0.59 0.9 0.35 0.21 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.37 -0.24 -0.66 8.1e+03 0.081 7.6e+02 1 ++
31 -0.59 0.9 0.35 0.21 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.37 -0.24 -0.66 8.1e+03 0.0051 7.6e+03 1 ++
32 -0.59 0.9 0.35 0.21 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.38 -0.24 -0.66 8.1e+03 0.00066 7.6e+04 1 ++
33 -0.59 0.9 0.35 0.21 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.38 -0.24 -0.66 8.1e+03 5.8e-06 7.6e+04 1 ++
Considering neighbor 0/20 for current solution
Considering neighbor 1/20 for current solution
Attempt 73/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000095
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2 -
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.29 -
2 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 2.5 1 ++
3 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 1.2 -4.3 -
4 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.62 -2.8 -
5 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.31 -1.1 -
6 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.31 0.23 +
7 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.16 -0.33 -
8 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.078 -0.051 -
9 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.039 0.022 -
10 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.02 0.038 -
11 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.0098 0.039 -
12 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.0049 0.036 -
13 -0.44 0.045 -0.2 -0.0092 -0.56 0.23 0.00043 -0.45 0.2 0.044 -0.08 -0.017 -0.006 0.018 9.2e+03 6.5 0.0049 0.39 +
14 -0.44 0.045 -0.2 -0.0092 -0.56 0.23 0.00043 -0.45 0.2 0.044 -0.08 -0.017 -0.006 0.018 9.2e+03 6.5 0.0024 -0.37 -
15 -0.44 0.048 -0.2 -0.0068 -0.56 0.22 -0.002 -0.45 0.2 0.046 -0.083 -0.014 -0.0084 0.021 9.1e+03 3.9 0.0024 0.54 +
16 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.024 1.3 ++
17 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.012 -2.9 -
18 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.0061 -3.6 -
19 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.0031 -3.1 -
20 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.0015 -2 -
21 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.00076 -1.3 -
22 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.00038 -0.19 -
23 -0.44 0.049 -0.19 -0.0064 -0.55 0.22 -0.0013 -0.45 0.2 0.047 -0.084 -0.015 -0.0088 0.021 9e+03 2.1 0.0038 1 ++
24 -0.44 0.049 -0.19 -0.0064 -0.55 0.22 -0.0011 -0.45 0.19 0.048 -0.084 -0.015 -0.0089 0.022 9e+03 5.9 0.0038 0.32 +
25 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.0038 0.17 +
26 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.0019 -2 -
27 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.00095 -1.7 -
28 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.00048 -1.1 -
29 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.00024 0.039 -
30 -0.44 0.051 -0.19 -0.0061 -0.55 0.22 -0.0012 -0.45 0.19 0.049 -0.085 -0.015 -0.0092 0.023 9e+03 2.1 0.0024 0.98 ++
31 -0.44 0.051 -0.19 -0.0061 -0.55 0.22 -0.0011 -0.45 0.19 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 5.6 0.0024 0.18 +
32 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0024 0.33 +
33 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0012 -2.7 -
34 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0006 -1.9 -
35 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0003 -1.3 -
36 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.00015 -0.18 -
37 -0.44 0.052 -0.19 -0.0059 -0.55 0.22 -0.0012 -0.46 0.18 0.049 -0.086 -0.015 -0.0094 0.024 9e+03 0.59 0.00015 0.86 +
38 -0.44 0.052 -0.19 -0.0059 -0.55 0.22 -0.0012 -0.46 0.18 0.05 -0.086 -0.015 -0.0094 0.024 9e+03 0.1 0.0015 0.99 ++
39 -0.44 0.053 -0.19 -0.0059 -0.55 0.22 -0.0012 -0.46 0.18 0.05 -0.087 -0.015 -0.0094 0.025 9e+03 0.14 0.015 1 ++
40 -0.43 0.057 -0.19 -0.0057 -0.55 0.21 -0.0011 -0.46 0.17 0.052 -0.089 -0.016 -0.0096 0.028 9e+03 0.094 0.15 1 ++
41 -0.41 0.099 -0.14 -0.0044 -0.53 0.17 -0.00097 -0.47 0.019 0.069 -0.12 -0.023 -0.012 0.052 8.9e+03 0.064 1.5 0.97 ++
42 -1.2 1.3 0.36 0.35 -0.78 0.11 -0.00072 -0.92 -0.66 -0.42 -0.35 -0.021 -0.26 -0.25 8.3e+03 0.24 15 1.1 ++
43 -1.2 1.3 0.36 0.35 -0.78 0.11 -0.00072 -0.92 -0.66 -0.42 -0.35 -0.021 -0.26 -0.25 8.3e+03 0.24 0.34 -3.7 -
44 -1.3 1.3 0.34 0.36 -1.1 -0.046 -7.3e-05 -0.97 -0.78 -0.44 -0.46 -0.096 -0.27 -0.3 8.3e+03 0.49 3.4 0.94 ++
45 -1.1 1.1 0.54 0.56 -1.7 -0.08 7.7e-05 -1.1 -0.75 -0.25 -0.96 -0.056 -0.4 -0.34 8.2e+03 1.5 34 1.2 ++
46 -1.1 1.1 0.54 0.56 -1.7 -0.08 7.7e-05 -1.1 -0.75 -0.25 -0.96 -0.056 -0.4 -0.34 8.2e+03 1.5 0.31 -0.12 -
47 -1.1 1.2 0.55 0.56 -2 -0.11 0.00022 -1.1 -0.76 -0.22 -0.98 -0.051 -0.4 -0.37 8.1e+03 10 0.31 0.73 +
48 -0.97 1.2 0.55 0.57 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.077 -0.44 -0.34 8.1e+03 2 3.1 0.95 ++
49 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.08 -0.46 -0.34 8.1e+03 0.027 31 0.99 ++
50 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.08 -0.47 -0.34 8.1e+03 1e-05 3.1e+02 1 ++
51 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.08 -0.47 -0.34 8.1e+03 6.5e-07 3.1e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 74/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000096
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.83 0.039 -1 1.1 -0.19 1.3 -0.023 -0.094 9e+03 0.063 1 0.69 +
1 -0.59 1 -1.2 0.83 -0.98 1.4 -0.15 -0.48 8.3e+03 0.016 10 0.91 ++
2 -0.45 1.3 -1.7 0.21 -0.71 1.3 0.15 -1.2 8.3e+03 0.0092 10 0.74 +
3 -0.71 1.5 -1.7 0.33 -0.72 1.1 0.16 -1.2 8.2e+03 0.0041 1e+02 1.1 ++
4 -0.81 1.6 -1.6 0.37 -0.72 1.1 0.15 -1.2 8.2e+03 0.00024 1e+03 1 ++
5 -0.87 1.6 -1.6 0.37 -0.72 1 0.16 -1.2 8.2e+03 0.00027 1e+04 1 ++
6 -0.87 1.6 -1.6 0.37 -0.72 1 0.16 -1.2 8.2e+03 8e-07 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 75/100
Considering neighbor 0/20 for current solution
Attempt 76/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000097
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2.3 -
1 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.42 -
2 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 2.5 1.1 ++
3 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 1.2 -6.2 -
4 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.62 -4.7 -
5 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.31 -1.8 -
6 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.16 -0.27 -
7 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.16 0.15 +
8 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.078 -0.79 -
9 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.039 -0.7 -
10 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.02 -0.64 -
11 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.0098 -0.58 -
12 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.0049 -0.11 -
13 -0.35 -0.17 -0.0075 -0.41 -0.085 0.12 0.0012 -0.35 0.22 0.026 -0.012 -0.004 0.0067 9.2e+03 5.2 0.0049 0.32 +
14 -0.35 -0.17 -0.0075 -0.41 -0.085 0.12 0.0012 -0.35 0.22 0.026 -0.012 -0.004 0.0067 9.2e+03 5.2 0.0024 -0.5 -
15 -0.35 -0.17 -0.0099 -0.41 -0.083 0.12 -0.0013 -0.35 0.22 0.029 -0.015 -0.0065 0.0092 9.1e+03 4.1 0.0024 0.66 +
16 -0.35 -0.17 -0.0099 -0.41 -0.083 0.12 -0.00079 -0.36 0.22 0.029 -0.015 -0.0065 0.0096 9.1e+03 1.4 0.024 1.4 ++
17 -0.36 -0.16 -0.0099 -0.43 -0.086 0.13 -0.0008 -0.37 0.19 0.033 -0.016 -0.0071 0.014 9.1e+03 0.65 0.24 1 ++
18 -0.42 -0.12 -0.0095 -0.62 -0.11 0.25 -0.0013 -0.49 -0.05 0.065 -0.041 -0.013 0.049 8.9e+03 0.87 2.4 0.93 ++
19 -0.42 -0.12 -0.0095 -0.62 -0.11 0.25 -0.0013 -0.49 -0.05 0.065 -0.041 -0.013 0.049 8.9e+03 0.87 1.2 -35 -
20 -0.42 -0.12 -0.0095 -0.62 -0.11 0.25 -0.0013 -0.49 -0.05 0.065 -0.041 -0.013 0.049 8.9e+03 0.87 0.61 -3.4 -
21 -0.48 0.3 0.0091 -0.98 -0.096 0.027 -0.0003 -1 -0.66 -0.22 -0.36 -0.058 -0.15 8.5e+03 11 0.61 0.84 +
22 -0.48 0.3 0.0091 -0.98 -0.096 0.027 -0.0003 -1 -0.66 -0.22 -0.36 -0.058 -0.15 8.5e+03 11 0.31 -1.7 -
23 -0.48 0.3 0.0091 -0.98 -0.096 0.027 -0.0003 -1 -0.66 -0.22 -0.36 -0.058 -0.15 8.5e+03 11 0.15 -0.56 -
24 -0.48 0.3 0.0091 -0.98 -0.096 0.027 -0.0003 -1 -0.66 -0.22 -0.36 -0.058 -0.15 8.5e+03 11 0.076 0.067 -
25 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.076 0.14 +
26 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.038 -1.2 -
27 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.019 -1.2 -
28 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0095 -1.2 -
29 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0048 -1.2 -
30 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0024 -1.2 -
31 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0012 -0.74 -
32 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0006 -0.071 -
33 -0.52 0.3 0.012 -1.1 -0.12 0.061 -0.00058 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 5.6 0.0006 0.66 +
34 -0.52 0.3 0.012 -1.1 -0.12 0.061 -0.00058 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 5.6 0.0003 -2.5 -
35 -0.52 0.3 0.012 -1.1 -0.12 0.061 -0.00058 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 5.6 0.00015 -1.6 -
36 -0.52 0.3 0.012 -1.1 -0.12 0.061 -0.00058 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 5.6 7.5e-05 -0.54 -
37 -0.52 0.3 0.013 -1.1 -0.12 0.061 -0.00051 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 1.6 7.5e-05 0.72 +
38 -0.52 0.3 0.013 -1.1 -0.12 0.061 -0.00051 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 0.08 0.00075 1 ++
39 -0.52 0.3 0.013 -1.1 -0.12 0.06 -0.00051 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 0.029 0.0075 1 ++
40 -0.53 0.3 0.013 -1.1 -0.12 0.053 -0.00048 -1.1 -0.61 -0.22 -0.33 -0.063 -0.16 8.5e+03 0.066 0.075 1 ++
41 -0.55 0.31 0.019 -1.1 -0.13 -0.017 -0.00019 -1.2 -0.59 -0.22 -0.3 -0.07 -0.16 8.4e+03 0.12 0.075 0.89 +
42 -0.56 0.35 0.026 -1.2 -0.15 -0.015 -0.0002 -1.2 -0.58 -0.23 -0.28 -0.078 -0.19 8.4e+03 0.012 0.75 1 ++
43 -0.56 0.35 0.026 -1.2 -0.15 -0.015 -0.0002 -1.2 -0.58 -0.23 -0.28 -0.078 -0.19 8.4e+03 0.012 0.37 -1.8 -
44 -0.54 0.57 0.074 -1.5 -0.27 -0.12 0.00025 -1.6 -0.67 -0.25 -0.13 -0.13 -0.29 8.4e+03 20 0.37 0.48 +
45 -0.48 0.68 0.12 -1.9 -0.44 -0.09 0.00013 -1.6 -0.77 -0.29 -0.14 -0.16 -0.36 8.3e+03 16 0.37 0.79 +
46 -0.48 0.68 0.12 -1.9 -0.44 -0.09 0.00013 -1.6 -0.77 -0.29 -0.14 -0.16 -0.36 8.3e+03 16 0.19 -0.095 -
47 -0.45 0.73 0.19 -2.1 -0.59 -0.12 0.00026 -1.8 -0.75 -0.23 -0.097 -0.21 -0.34 8.3e+03 26 0.19 0.35 +
48 -0.38 0.73 0.3 -2.2 -0.78 -0.11 0.00019 -1.8 -0.85 -0.23 -0.15 -0.28 -0.35 8.2e+03 8.9 0.19 0.84 +
49 -0.33 0.73 0.45 -2.1 -0.96 -0.11 0.00021 -1.9 -0.81 -0.19 -0.12 -0.39 -0.37 8.2e+03 1 1.9 0.98 ++
50 -0.38 0.76 0.61 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.13 -0.59 -0.37 8.2e+03 0.049 19 1 ++
51 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 0.00083 1.9e+02 1 ++
52 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 0.00058 1.9e+03 1 ++
53 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 1.4e-05 1.9e+04 1 ++
54 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 0.0056 1.9e+05 1 ++
55 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 7.8e-07 1.9e+05 1 ++
Considering neighbor 0/20 for current solution
Attempt 77/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000098
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 -1 0.36 0.15 -0.62 -0.42 -0.96 -0.77 -0.64 -0.74 -0.71 0.021 -0.25 -0.41 -0.63 -0.67 8.6e+03 0.08 10 1.1 ++
1 -0.81 0.62 0.51 -0.98 -0.54 -1.5 -1 -0.83 -0.85 -0.59 -0.12 -0.57 -0.68 -0.76 -0.6 8.3e+03 0.022 1e+02 1.2 ++
2 -0.71 0.74 0.61 -1.1 -0.61 -1.7 -1 -0.87 -0.89 -0.63 -0.12 -0.59 -0.69 -0.79 -0.61 8.3e+03 0.0036 1e+03 1.1 ++
3 -0.69 0.75 0.63 -1.1 -0.63 -1.8 -1 -0.87 -0.89 -0.63 -0.12 -0.59 -0.69 -0.79 -0.61 8.3e+03 0.00011 1e+04 1 ++
4 -0.69 0.75 0.63 -1.1 -0.63 -1.8 -1 -0.87 -0.89 -0.63 -0.12 -0.59 -0.69 -0.79 -0.61 8.3e+03 1.2e-07 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 78/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000099
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.5 0.088 -0.0016 -1 -0.63 1.8 0.19 -0.1 -0.026 0.038 -0.63 9.2e+03 0.19 1 0.68 +
1 -0.5 0.088 -0.0016 -1 -0.63 1.8 0.19 -0.1 -0.026 0.038 -0.63 9.2e+03 0.19 0.5 -1.7 -
2 -0.5 0.088 -0.0016 -1 -0.63 1.8 0.19 -0.1 -0.026 0.038 -0.63 9.2e+03 0.19 0.25 -0.11 -
3 -0.38 0.2 0.0047 -1 -0.61 1.8 -0.056 -0.25 -0.036 -0.19 -0.45 8.4e+03 0.027 2.5 0.95 ++
4 -0.42 0.44 0.33 -1 -0.99 2 -0.29 -0.025 -0.44 -0.25 -0.6 8.3e+03 0.0049 25 1 ++
5 -0.45 0.51 0.35 -1.1 -1.2 1.6 -0.28 -0.039 -0.46 -0.3 -0.67 8.3e+03 0.0044 25 0.86 +
6 -0.46 0.52 0.34 -1.1 -1.2 1.6 -0.28 -0.039 -0.44 -0.3 -0.67 8.3e+03 0.00015 2.5e+02 1 ++
7 -0.46 0.52 0.34 -1.1 -1.2 1.6 -0.28 -0.039 -0.44 -0.3 -0.67 8.3e+03 2.2e-06 2.5e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 79/100
Considering neighbor 0/20 for current solution
Attempt 80/100
Biogeme parameters read from biogeme.toml.
Model with 6 unknown parameters [max: 50]
*** Estimate b07everything_000100
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_1st b_cost mu_existing asc_car Function Relgrad Radius Rho
0 -0.71 -0.66 -0.41 -1 1.6 0.39 8.9e+03 0.13 1 0.77 +
1 -0.71 -0.66 -0.41 -1 1.6 0.39 8.9e+03 0.13 0.5 -0.96 -
2 -0.42 -0.75 -0.57 -0.5 2 -0.067 8.5e+03 0.026 0.5 0.81 +
3 -0.4 -0.69 -0.52 -0.66 2.1 -0.00045 8.5e+03 0.0014 5 0.98 ++
4 -0.41 -0.72 -0.54 -0.68 2 0.0087 8.5e+03 0.00037 50 0.95 ++
5 -0.41 -0.72 -0.54 -0.68 2 0.0087 8.5e+03 2.8e-06 50 1 ++
Considering neighbor 0/20 for current solution
Attempt 81/100
Considering neighbor 0/20 for current solution
Attempt 82/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000101
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 0.0014 -
1 -0.38 -0.18 -0.008 -0.5 -0.38 1.3 0.28 -0.0093 -0.033 -0.0044 -0.035 9.2e+03 0.12 0.5 0.73 +
2 -0.34 0.051 -0.0015 -0.77 -0.49 1.3 -0.22 -0.073 -0.14 -0.018 -0.088 8.7e+03 0.045 5 0.93 ++
3 -0.28 0.62 0.58 -0.97 -1.3 1.8 -0.75 -0.57 -0.066 -0.37 -0.38 8.5e+03 0.04 5 0.85 +
4 -0.25 0.44 0.38 -0.99 -1.4 1.8 -0.85 -0.49 -0.13 -0.55 -0.48 8.4e+03 0.0041 50 1.1 ++
5 -0.25 0.44 0.38 -0.99 -1.4 1.8 -0.85 -0.49 -0.13 -0.55 -0.48 8.4e+03 0.0041 0.38 -1.5 -
6 -0.29 0.44 0.37 -1.1 -1.5 1.4 -0.83 -0.46 -0.11 -0.55 -0.44 8.4e+03 0.01 0.38 0.77 +
7 -0.43 0.57 0.5 -1.2 -1.6 1.3 -0.84 -0.43 -0.12 -0.56 -0.41 8.4e+03 0.0033 3.8 1.2 ++
8 -0.58 0.69 0.6 -1.3 -1.7 1.1 -0.83 -0.39 -0.11 -0.55 -0.38 8.4e+03 0.0041 38 1.1 ++
9 -0.65 0.74 0.65 -1.3 -1.7 1 -0.82 -0.38 -0.1 -0.54 -0.37 8.4e+03 0.00061 3.8e+02 1.1 ++
10 -0.68 0.76 0.65 -1.3 -1.8 1 -0.82 -0.37 -0.1 -0.54 -0.36 8.4e+03 0.00031 3.8e+03 1.1 ++
11 -0.68 0.76 0.65 -1.3 -1.8 1 -0.82 -0.37 -0.1 -0.54 -0.36 8.4e+03 0.00023 3.8e+04 1 ++
12 -0.68 0.76 0.65 -1.3 -1.8 1 -0.82 -0.37 -0.1 -0.54 -0.36 8.4e+03 1.4e-06 3.8e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 83/100
Considering neighbor 0/20 for current solution
Attempt 84/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000102
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di b_cost mu_public b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.4 0.5 -0.2 -
1 -0.28 -0.5 -0.073 -0.095 1.2 0.22 0.061 -0.054 -0.14 -0.051 9.3e+03 0.057 0.5 0.86 +
2 0.061 -0.84 -0.3 -0.6 1 -0.28 0.061 0.21 -0.3 -0.3 9.2e+03 0.14 5 1.5 ++
3 0.061 -0.84 -0.3 -0.6 1 -0.28 0.061 0.21 -0.3 -0.3 9.2e+03 0.14 2.5 -15 -
4 0.061 -0.84 -0.3 -0.6 1 -0.28 0.061 0.21 -0.3 -0.3 9.2e+03 0.14 1.2 -1.3 -
5 -0.16 -1.4 -0.36 -0.88 2.2 -1.5 0.19 -0.61 -1.2 -0.42 8.9e+03 0.12 1.2 0.27 +
6 -0.26 -1.2 -0.026 -0.79 1 -1 0.49 -0.55 -0.66 -0.27 8.6e+03 0.079 1.2 0.61 +
7 -0.27 -1.6 -0.11 -0.77 1 -1.5 0.7 -0.46 -1 -0.012 8.5e+03 0.015 12 1.1 ++
8 -0.1 -1.9 0.81 -0.8 1 -1.7 2.4 -0.48 -1.2 1.1 8.5e+03 0.0079 12 0.26 +
9 -0.13 -1.9 0.35 -0.8 1 -1.8 1.4 -0.63 -1.1 0.65 8.5e+03 0.01 12 0.61 +
10 -0.1 -1.9 0.45 -0.8 1 -1.8 1.7 -0.52 -1.2 0.66 8.5e+03 0.00089 1.2e+02 0.91 ++
11 -0.1 -1.9 0.42 -0.81 1 -1.8 1.6 -0.53 -1.2 0.62 8.5e+03 5.9e-05 1.2e+03 0.97 ++
12 -0.1 -1.9 0.42 -0.81 1 -1.8 1.6 -0.53 -1.2 0.62 8.5e+03 9.6e-08 1.2e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 85/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000103
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 -0.8 0.77 -0.74 -0.13 -0.85 -1 0.3 -0.6 -0.32 -0.58 -0.78 -0.029 -0.66 8.4e+03 0.09 10 1.1 ++
1 -0.94 1.3 -1.3 0.62 -0.97 -1.6 2.1 -0.74 -0.44 -0.88 -1.2 0.91 -0.62 8.2e+03 0.025 1e+02 1 ++
2 -0.85 1.3 -1.5 0.054 -1 -1.8 1.1 -0.75 -0.54 -0.99 -1.2 0.36 -0.67 8.2e+03 0.012 1e+02 0.28 +
3 -0.85 1.3 -1.5 0.054 -1 -1.8 1.1 -0.75 -0.54 -0.99 -1.2 0.36 -0.67 8.2e+03 0.012 0.6 0.058 -
4 -0.78 1.3 -1.4 0.26 -1 -1.5 1.7 -0.73 -0.38 -0.98 -1.2 0.64 -0.62 8.2e+03 0.0091 0.6 0.41 +
5 -0.81 1.3 -1.5 0.25 -1 -1.8 1.5 -0.75 -0.5 -0.99 -1.2 0.57 -0.65 8.1e+03 0.0028 0.6 0.79 +
6 -0.81 1.3 -1.5 0.31 -1 -1.8 1.6 -0.76 -0.5 -0.99 -1.2 0.64 -0.65 8.1e+03 2.4e-05 6 0.98 ++
7 -0.81 1.3 -1.5 0.31 -1 -1.8 1.6 -0.76 -0.5 -0.99 -1.2 0.64 -0.65 8.1e+03 3.9e-08 6 1 ++
Considering neighbor 0/20 for current solution
Attempt 86/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000104
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.26 -
1 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.5 0.64 +
2 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.25 -8.2 -
3 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.12 -10 -
4 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.062 -13 -
5 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.031 -29 -
6 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.016 -2.3 -
7 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.16 0.97 ++
8 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.078 -14 -
9 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.039 -13 -
10 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.02 -12 -
11 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.0098 -13 -
12 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.0049 -4.1 -
13 -0.27 -0.12 0.0052 -0.52 -0.092 -0.0088 -0.0011 -0.059 0.18 0.067 -0.013 -0.027 -0.022 -0.01 -0.011 9.4e+03 1.8 0.0049 0.71 +
14 -0.27 -0.12 0.0053 -0.52 -0.092 -0.0068 -0.00074 -0.062 0.18 0.068 -0.016 -0.029 -0.022 -0.015 -0.012 9.4e+03 0.46 0.049 1 ++
15 -0.28 -0.11 0.0056 -0.54 -0.097 0.013 -0.00052 -0.095 0.19 0.076 -0.04 -0.047 -0.024 -0.064 -0.026 9.3e+03 0.29 0.49 1 ++
16 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.49 0.5 +
17 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.24 -6.9 -
18 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.12 -7.6 -
19 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.061 -14 -
20 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.031 -5.5 -
21 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.015 -3.6 -
22 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.0076 -2.6 -
23 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.0038 -1.6 -
24 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.0019 -0.28 -
25 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.0019 0.8 +
26 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.00095 -0.7 -
27 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.00048 -0.45 -
28 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.00024 0.021 -
29 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0011 -0.59 -0.11 0.15 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 0.79 0.00024 0.82 +
30 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0011 -0.59 -0.11 0.15 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 0.14 0.0024 1 ++
31 -0.33 0.048 0.015 -0.75 -0.16 0.21 -0.0011 -0.59 -0.12 0.15 -0.13 -0.16 -0.041 -0.41 -0.19 8.9e+03 0.7 0.024 1 ++
32 -0.33 0.052 0.015 -0.75 -0.16 0.2 -0.0011 -0.59 -0.14 0.15 -0.13 -0.15 -0.041 -0.39 -0.19 8.8e+03 0.11 0.24 1 ++
33 -0.33 0.12 0.019 -0.76 -0.17 0.28 -0.0014 -0.64 -0.38 0.16 -0.083 -0.13 -0.045 -0.33 -0.19 8.6e+03 0.48 0.24 0.81 +
34 -0.34 0.26 0.032 -0.72 -0.2 0.4 -0.0019 -0.71 -0.62 0.31 -0.14 -0.17 -0.06 -0.44 -0.2 8.5e+03 0.32 0.24 0.83 +
35 -0.48 0.35 0.051 -0.79 -0.18 0.3 -0.0015 -0.76 -0.57 0.55 -0.21 -0.2 -0.082 -0.44 -0.09 8.5e+03 0.27 0.24 0.85 +
36 -0.66 0.51 0.1 -0.84 -0.078 0.36 -0.0018 -0.77 -0.81 0.64 -0.33 -0.19 -0.12 -0.5 0.096 8.4e+03 0.38 0.24 0.85 +
37 -0.8 0.6 0.15 -0.87 -0.0017 0.33 -0.0016 -0.78 -0.85 0.88 -0.34 -0.11 -0.16 -0.53 0.12 8.4e+03 0.91 0.24 0.74 +
38 -0.99 0.76 0.29 -1.1 0.083 0.17 -0.00098 -0.79 -1.1 0.88 -0.49 -0.15 -0.23 -0.64 0.14 8.4e+03 0.074 0.24 0.84 +
39 -1 0.88 0.48 -1.2 0.14 0.12 -0.00077 -0.78 -1.2 1.1 -0.42 -0.081 -0.31 -0.79 0.34 8.4e+03 0.012 2.4 1.1 ++
40 -1 0.88 0.48 -1.2 0.14 0.12 -0.00077 -0.78 -1.2 1.1 -0.42 -0.081 -0.31 -0.79 0.34 8.4e+03 0.012 0.55 -32 -
41 -1 0.88 0.48 -1.2 0.14 0.12 -0.00077 -0.78 -1.2 1.1 -0.42 -0.081 -0.31 -0.79 0.34 8.4e+03 0.012 0.28 -1.1 -
42 -1 0.86 0.67 -1.5 0.23 0.017 -0.00034 -0.79 -1.5 1.2 -0.49 -0.1 -0.38 -0.96 0.28 8.4e+03 0.22 2.8 1 ++
43 -0.81 0.92 0.88 -2 0.28 -0.054 -4.5e-05 -0.8 -1.9 1.4 -0.42 -0.1 -0.46 -1.3 0.34 8.3e+03 0.8 28 1.2 ++
44 -0.58 0.91 0.85 -2.5 0.2 -0.088 0.00011 -0.8 -2.2 1.2 -0.38 -0.1 -0.48 -1.6 0.21 8.3e+03 0.2 2.8e+02 1.3 ++
45 -0.39 0.89 0.82 -2.8 0.028 -0.1 0.00017 -0.8 -2.4 0.91 -0.35 -0.11 -0.5 -1.7 -0.0096 8.3e+03 1.4 2.8e+03 1.1 ++
46 -0.43 0.9 0.8 -2.8 -0.096 -0.099 0.00016 -0.8 -2.4 0.7 -0.36 -0.11 -0.52 -1.7 -0.16 8.3e+03 0.12 2.8e+04 0.99 ++
47 -0.42 0.9 0.8 -2.8 -0.099 -0.1 0.00016 -0.8 -2.4 0.7 -0.35 -0.11 -0.52 -1.7 -0.17 8.3e+03 0.038 2.8e+05 1 ++
48 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.51 -1.7 -0.18 8.3e+03 0.067 2.8e+06 1 ++
49 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 0.00016 2.8e+07 1 ++
50 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 0.00035 2.8e+08 1 ++
51 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 1.4e-05 2.8e+09 1 ++
52 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 4.2e-07 2.8e+09 1 ++
Considering neighbor 0/20 for current solution
Attempt 87/100
Biogeme parameters read from biogeme.toml.
Model with 17 unknown parameters [max: 50]
*** Estimate b07everything_000105
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.48 -
1 1e+04 1.4 0.5 0.2 +
2 1e+04 1.4 0.25 -5.5 -
3 1e+04 1.4 0.12 -6.3 -
4 1e+04 1.4 0.062 -3.9 -
5 9.6e+03 6.2 0.062 0.87 +
6 9.6e+03 6.2 0.031 -0.071 -
7 9.6e+03 6.2 0.016 -0.071 -
8 9.6e+03 6.2 0.0078 -0.077 -
9 9.5e+03 1.7 0.0078 0.19 +
10 9.5e+03 1.7 0.0039 -0.016 -
11 9.4e+03 1 0.039 0.96 ++
12 9.4e+03 0.063 0.39 1 ++
13 9e+03 2 3.9 0.93 ++
14 9e+03 2 2 -13 -
15 9e+03 2 0.98 -4.4 -
16 9e+03 2 0.49 -0.6 -
17 8.6e+03 2.7 0.49 0.51 +
18 8.4e+03 2.9 4.9 0.92 ++
19 8.4e+03 2.9 0.59 -52 -
20 8.3e+03 2.3 0.59 0.59 +
21 8.3e+03 2.3 0.29 -0.72 -
22 8.3e+03 2.3 0.15 -0.24 -
23 8.3e+03 2.3 0.073 -0.034 -
24 8.3e+03 2.3 0.037 -0.05 -
25 8.3e+03 2.3 0.018 -0.42 -
26 8.3e+03 2.3 0.0091 -0.75 -
27 8.3e+03 2.3 0.0046 -1.2 -
28 8.3e+03 2.3 0.0023 -1.7 -
29 8.3e+03 2.3 0.0011 -2 -
30 8.3e+03 2.3 0.00057 -2.3 -
31 8.3e+03 2.3 0.00029 -1.8 -
32 8.3e+03 2.3 0.00014 -0.36 -
33 8.3e+03 0.54 0.00014 0.69 +
34 8.3e+03 0.024 0.0014 1 ++
35 8.3e+03 0.097 0.014 1 ++
36 8.3e+03 0.019 0.14 1 ++
37 8.3e+03 0.015 0.14 0.69 +
38 8.3e+03 0.018 1.4 0.99 ++
39 8.3e+03 0.018 0.71 -1.9e+02 -
40 8.3e+03 0.018 0.36 -42 -
41 8.3e+03 0.018 0.18 -1.4 -
42 8.3e+03 0.4 1.8 1 ++
43 8.3e+03 0.91 1.8 0.28 +
44 8.2e+03 0.7 18 0.96 ++
45 8.2e+03 0.7 8.9 -3.3e+02 -
46 8.2e+03 0.7 4.5 -2.8e+02 -
47 8.2e+03 0.7 2.2 -2e+02 -
48 8.2e+03 0.7 1.1 -90 -
49 8.2e+03 0.7 0.56 -23 -
50 8.2e+03 0.7 0.28 -4.6 -
51 8.2e+03 2.8 0.28 0.3 +
52 8.2e+03 11 2.8 0.94 ++
53 8.2e+03 11 1.4 -85 -
54 8.2e+03 11 0.7 -17 -
55 8.2e+03 11 0.35 -6.6 -
56 8.2e+03 11 0.17 -1.8 -
57 8.2e+03 11 0.087 -0.79 -
58 8.2e+03 11 0.044 -0.68 -
59 8.2e+03 11 0.022 -1 -
60 8.2e+03 11 0.011 -0.51 -
61 8.2e+03 11 0.0054 -0.51 -
62 8.2e+03 11 0.0027 -0.54 -
63 8.2e+03 11 0.0014 -0.56 -
64 8.2e+03 11 0.00068 -0.58 -
65 8.2e+03 11 0.00034 -0.59 -
66 8.2e+03 11 0.00017 -0.59 -
67 8.2e+03 11 8.5e-05 -0.6 -
68 8.2e+03 11 4.3e-05 -0.44 -
69 8.2e+03 4.1 4.3e-05 0.58 +
70 8.2e+03 0.35 0.00043 0.94 ++
71 8.2e+03 0.0067 0.0043 1 ++
72 8.2e+03 0.03 0.043 0.99 ++
73 8.2e+03 5.5 0.43 0.98 ++
74 8.2e+03 1.1 0.43 0.55 +
75 8.2e+03 6 4.3 0.9 ++
76 8.2e+03 0.21 43 1 ++
77 8.2e+03 0.0055 4.3e+02 1 ++
78 8.2e+03 3e-05 4.3e+03 1 ++
79 8.2e+03 1.2e-06 4.3e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 88/100
Considering neighbor 0/20 for current solution
Attempt 89/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000106
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.45 -
1 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.5 0.28 +
2 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.25 -5.9 -
3 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.12 -7 -
4 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.062 -5.2 -
5 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.031 -0.15 -
6 -0.24 -0.47 -0.073 -0.026 0.019 -0.24 0.17 0.062 0.21 0.016 0.0094 0.0094 -0.014 9.6e+03 0.98 0.031 0.84 +
7 -0.24 -0.47 -0.073 -0.026 0.019 -0.24 0.17 0.062 0.21 0.016 0.0094 0.0094 -0.014 9.6e+03 0.98 0.016 -3.7 -
8 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.16 0.92 ++
9 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.078 -13 -
10 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.039 -13 -
11 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.02 -13 -
12 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.0098 -13 -
13 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.0049 -6 -
14 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.0024 0.039 -
15 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.024 0.96 ++
16 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.012 -0.93 -
17 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.0061 -0.8 -
18 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.0031 -0.99 -
19 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.0015 -1.4 -
20 -0.23 -0.46 -0.085 -0.038 -0.00058 -0.26 0.15 0.082 0.19 -0.0037 -0.01 -0.0063 -0.034 9.4e+03 0.43 0.0015 0.77 +
21 -0.23 -0.46 -0.085 -0.037 -0.00038 -0.26 0.15 0.082 0.19 -0.004 -0.011 -0.0069 -0.034 9.4e+03 0.13 0.015 1 ++
22 -0.23 -0.47 -0.087 -0.031 -0.00019 -0.27 0.14 0.086 0.18 -0.0074 -0.022 -0.013 -0.039 9.3e+03 0.042 0.15 1 ++
23 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.15 0.89 +
24 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.076 -8.7 -
25 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.038 -9.7 -
26 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.019 -12 -
27 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.0095 -5.9 -
28 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.0048 -4.3 -
29 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.0024 -2.3 -
30 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.0012 -0.1 -
31 -0.26 -0.54 -0.11 0.03 -0.00025 -0.36 0.052 0.12 0.021 -0.042 -0.13 -0.078 -0.095 9.1e+03 1.1 0.012 0.97 ++
32 -0.26 -0.55 -0.12 0.035 -0.00055 -0.37 0.04 0.13 0.01 -0.045 -0.14 -0.083 -0.098 9.1e+03 1.5 0.012 0.9 +
33 -0.26 -0.55 -0.12 0.041 -0.00039 -0.37 0.028 0.13 -0.00047 -0.047 -0.15 -0.087 -0.1 9.1e+03 0.65 0.12 0.97 ++
34 -0.25 -0.57 -0.13 0.11 -0.00077 -0.43 -0.091 0.15 -0.1 -0.069 -0.23 -0.13 -0.14 8.9e+03 1.8 1.2 0.98 ++
35 -0.25 -0.57 -0.13 0.11 -0.00077 -0.43 -0.091 0.15 -0.1 -0.069 -0.23 -0.13 -0.14 8.9e+03 1.8 0.6 -2.5 -
36 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.6 0.12 +
37 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.3 -5.2 -
38 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.15 -5.6 -
39 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.075 -4.5 -
40 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.037 -2.9 -
41 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.019 -2.2 -
42 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.0093 -1.8 -
43 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.0047 -1.3 -
44 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.0023 -0.8 -
45 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.0012 -0.35 -
46 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.00058 -0.18 -
47 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.00029 0.05 -
48 -0.25 -0.71 -0.21 0.6 -0.0028 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 4.8 0.00029 0.51 +
49 -0.25 -0.71 -0.21 0.6 -0.0028 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 4.8 0.00015 -0.8 -
50 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 8.4 0.00015 0.17 +
51 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 8.4 7.3e-05 0.056 -
52 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 2.3 7.3e-05 0.61 +
53 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 0.79 7.3e-05 0.89 +
54 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 0.17 0.00073 1 ++
55 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 1.3 0.0073 1 ++
56 -0.25 -0.71 -0.21 0.59 -0.0027 -0.75 -0.69 0.23 -0.46 -0.18 -0.62 -0.27 -0.29 8.8e+03 0.15 0.073 1 ++
57 -0.24 -0.68 -0.2 0.53 -0.0025 -0.76 -0.72 0.23 -0.49 -0.17 -0.55 -0.26 -0.27 8.6e+03 0.26 0.73 1 ++
58 -0.24 -0.76 -0.17 0.12 -0.00079 -1.5 -0.88 0.74 -0.56 -0.49 -0.65 -0.0046 -0.48 8.4e+03 0.79 7.3 0.91 ++
59 -0.24 -0.76 -0.17 0.12 -0.00079 -1.5 -0.88 0.74 -0.56 -0.49 -0.65 -0.0046 -0.48 8.4e+03 0.79 0.35 -2.9 -
60 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 3.5 0.95 ++
61 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 1.8 -1.8e+02 -
62 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 0.88 -89 -
63 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 0.44 -20 -
64 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 0.22 -1.5 -
65 -0.19 -1 0.073 0.059 -0.00051 -1.9 -1.3 1.1 -0.77 -0.51 -0.92 0.29 -0.6 8.3e+03 0.26 0.22 0.82 +
66 -0.082 -1.2 0.15 0.035 -0.00042 -1.9 -1.5 1.2 -0.82 -0.59 -1 0.27 -0.62 8.3e+03 0.21 2.2 1.1 ++
67 -0.082 -1.2 0.15 0.035 -0.00042 -1.9 -1.5 1.2 -0.82 -0.59 -1 0.27 -0.62 8.3e+03 0.21 1.1 -1.9e+02 -
68 -0.082 -1.2 0.15 0.035 -0.00042 -1.9 -1.5 1.2 -0.82 -0.59 -1 0.27 -0.62 8.3e+03 0.21 0.55 -27 -
69 -0.082 -1.2 0.15 0.035 -0.00042 -1.9 -1.5 1.2 -0.82 -0.59 -1 0.27 -0.62 8.3e+03 0.21 0.27 -1.7 -
70 -0.02 -1.5 0.11 -0.034 -0.00013 -1.9 -1.7 1.3 -0.75 -0.46 -1.3 0.33 -0.64 8.3e+03 0.063 2.7 0.95 ++
71 -0.02 -1.5 0.11 -0.034 -0.00013 -1.9 -1.7 1.3 -0.75 -0.46 -1.3 0.33 -0.64 8.3e+03 0.063 0.42 -2.1 -
72 0.17 -1.9 0.25 -0.071 3e-05 -1.9 -2 1.2 -0.79 -0.57 -1.5 0.23 -0.62 8.3e+03 0.73 4.2 1.2 ++
73 0.17 -1.9 0.25 -0.071 3e-05 -1.9 -2 1.2 -0.79 -0.57 -1.5 0.23 -0.62 8.3e+03 0.73 0.38 -1.3 -
74 0.31 -2.3 0.065 -0.1 0.00018 -1.9 -2.3 1.1 -0.78 -0.4 -1.8 0.14 -0.66 8.3e+03 3 3.8 0.91 ++
75 0.46 -2.5 -0.056 -0.1 0.00018 -1.9 -2.4 0.91 -0.8 -0.43 -1.9 0.0095 -0.66 8.3e+03 0.88 38 1 ++
76 0.43 -2.4 -0.24 -0.1 0.00018 -1.9 -2.4 0.59 -0.79 -0.44 -1.9 -0.23 -0.65 8.3e+03 0.065 3.8e+02 1 ++
77 0.45 -2.5 -0.25 -0.11 0.00019 -1.9 -2.4 0.58 -0.8 -0.43 -1.9 -0.24 -0.65 8.3e+03 0.024 3.8e+03 0.99 ++
78 0.45 -2.5 -0.26 -0.11 0.00019 -1.9 -2.4 0.56 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.00043 3.8e+04 1 ++
79 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.029 3.8e+05 1 ++
80 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 8.1e-05 3.8e+06 1 ++
81 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.0004 3.8e+07 1 ++
82 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 1.1e-05 3.8e+08 1 ++
83 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.001 3.8e+09 1 ++
84 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 2.6e-07 3.8e+09 1 ++
Considering neighbor 0/20 for current solution
Attempt 90/100
Considering neighbor 0/20 for current solution
Attempt 91/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000107
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.19 -
1 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.5 0.77 +
2 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.25 -8.3 -
3 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.12 -10 -
4 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.062 -13 -
5 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.031 -76 -
6 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.016 -5.8 -
7 -0.29 -0.52 -0.083 0.0097 -0.0024 -0.054 0.19 0.062 -0.0082 -0.0085 -0.0059 9.4e+03 5.2 0.016 0.53 +
8 -0.29 -0.52 -0.085 0.013 6.9e-06 -0.062 0.19 0.065 -0.015 -0.024 -0.012 9.4e+03 0.27 0.016 0.8 +
9 -0.29 -0.53 -0.087 0.019 -0.0011 -0.072 0.19 0.067 -0.022 -0.04 -0.017 9.3e+03 1 0.016 0.88 +
10 -0.29 -0.54 -0.088 0.026 -0.00076 -0.084 0.19 0.07 -0.029 -0.055 -0.021 9.3e+03 0.49 0.16 1 ++
11 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.16 0.63 +
12 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.078 -8.1 -
13 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.039 -10 -
14 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.02 -6.9 -
15 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.0098 -4.5 -
16 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.0049 -3.1 -
17 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.0024 -1.5 -
18 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.0012 0.099 -
19 -0.32 -0.61 -0.11 0.091 -0.0006 -0.21 0.16 0.099 -0.092 -0.21 -0.073 9.1e+03 1.6 0.012 0.98 ++
20 -0.32 -0.61 -0.11 0.088 -0.0007 -0.22 0.15 0.1 -0.089 -0.21 -0.074 9.1e+03 0.44 0.12 0.99 ++
21 -0.32 -0.62 -0.12 0.063 -0.00052 -0.3 0.027 0.1 -0.062 -0.17 -0.087 9e+03 0.047 1.2 1 ++
22 -0.32 -0.62 -0.12 0.063 -0.00052 -0.3 0.027 0.1 -0.062 -0.17 -0.087 9e+03 0.047 0.61 -0.39 -
23 -0.33 -0.79 -0.19 0.46 -0.0022 -0.77 -0.58 0.19 -0.18 -0.57 -0.25 8.7e+03 3.4 0.61 0.41 +
24 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 6.1 0.9 ++
25 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 3.1 -2.7e+03 -
26 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 1.5 -1e+03 -
27 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 0.76 -3.2e+02 -
28 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 0.38 -17 -
29 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 0.19 -0.3 -
30 -0.36 -0.89 -0.099 0.32 -0.0016 -0.76 -0.92 0.68 -0.35 -0.58 0.076 8.5e+03 0.6 0.19 0.39 +
31 -0.38 -0.94 -0.0086 0.25 -0.0013 -0.79 -0.91 0.87 -0.43 -0.57 0.11 8.5e+03 0.095 0.19 0.83 +
32 -0.45 -1.1 0.13 0.15 -0.00091 -0.8 -1.1 0.99 -0.53 -0.67 0.23 8.5e+03 0.022 1.9 1 ++
33 -0.45 -1.1 0.13 0.15 -0.00091 -0.8 -1.1 0.99 -0.53 -0.67 0.23 8.5e+03 0.022 0.29 -0.91 -
34 -0.31 -1.4 0.14 0.06 -0.00052 -0.78 -1.4 1.3 -0.43 -0.89 0.31 8.5e+03 0.04 2.9 1.1 ++
35 -0.12 -1.8 0.28 -0.015 -0.0002 -0.8 -1.7 1.4 -0.46 -1.1 0.4 8.4e+03 0.4 29 1.3 ++
36 0.068 -2.3 0.25 -0.074 4e-05 -0.8 -2.1 1.4 -0.44 -1.4 0.33 8.4e+03 1.7 2.9e+02 1.3 ++
37 0.28 -2.8 0.16 -0.099 0.00016 -0.8 -2.4 1.2 -0.42 -1.7 0.18 8.4e+03 0.58 2.9e+03 1.1 ++
38 0.39 -3 -0.0013 -0.1 0.00017 -0.8 -2.4 0.9 -0.4 -1.8 -0.003 8.4e+03 0.072 2.9e+04 1 ++
39 0.34 -2.9 -0.049 -0.099 0.00016 -0.8 -2.4 0.8 -0.41 -1.7 -0.085 8.4e+03 0.15 2.9e+05 0.99 ++
40 0.37 -2.9 -0.083 -0.1 0.00017 -0.8 -2.4 0.74 -0.4 -1.7 -0.12 8.4e+03 0.041 2.9e+06 0.99 ++
41 0.36 -2.9 -0.097 -0.099 0.00016 -0.8 -2.4 0.72 -0.41 -1.7 -0.15 8.4e+03 0.011 2.9e+07 1 ++
42 0.37 -2.9 -0.11 -0.1 0.00017 -0.8 -2.4 0.7 -0.41 -1.7 -0.16 8.4e+03 0.0041 2.9e+08 1 ++
43 0.36 -2.9 -0.11 -0.1 0.00017 -0.8 -2.4 0.69 -0.41 -1.7 -0.17 8.4e+03 0.00085 2.9e+09 1 ++
44 0.36 -2.9 -0.11 -0.1 0.00017 -0.8 -2.4 0.69 -0.41 -1.7 -0.17 8.4e+03 0.00036 1e+10 1 ++
45 0.36 -2.9 -0.12 -0.1 0.00017 -0.8 -2.4 0.69 -0.41 -1.7 -0.17 8.4e+03 7.3e-05 1e+10 1 ++
46 0.36 -2.9 -0.12 -0.1 0.00017 -0.8 -2.4 0.68 -0.41 -1.7 -0.17 8.4e+03 3.2e-05 1e+10 1 ++
47 0.36 -2.9 -0.12 -0.1 0.00017 -0.8 -2.4 0.68 -0.41 -1.7 -0.17 8.4e+03 6.4e-06 1e+10 1 ++
48 0.36 -2.9 -0.12 -0.1 0.00017 -0.8 -2.4 0.68 -0.41 -1.7 -0.17 8.4e+03 2.8e-06 1e+10 1 ++
Considering neighbor 0/20 for current solution
Attempt 92/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000108
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_public asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.78 0.077 -0.33 -0.016 -1 -0.11 -0.24 1.5 -0.074 -0.11 -0.1 -0.0096 9.4e+03 0.12 1 0.46 +
1 -0.41 1.1 0.62 0.013 -1.1 -0.14 -1 1.8 -0.16 -0.46 -0.27 -0.047 9e+03 0.18 1 0.19 +
2 -0.41 1.1 0.62 0.013 -1.1 -0.14 -1 1.8 -0.16 -0.46 -0.27 -0.047 9e+03 0.18 0.5 -0.13 -
3 -0.66 0.58 0.17 0.087 -0.74 -0.17 -0.75 2.1 -0.039 -0.5 -0.11 -0.07 8.4e+03 0.049 0.5 0.68 +
4 -0.62 0.76 0.21 0.32 -0.86 -0.33 -0.68 1.9 -0.19 -1 -0.024 -0.2 8.3e+03 0.0041 5 1.1 ++
5 -0.62 0.76 0.21 0.32 -0.86 -0.33 -0.68 1.9 -0.19 -1 -0.024 -0.2 8.3e+03 0.0041 0.45 -1.3 -
6 -0.83 0.95 0.31 0.3 -1 -0.22 -0.71 1.5 -0.043 -1.2 -0.11 -0.28 8.3e+03 0.0087 4.5 0.98 ++
7 -1 1.1 0.39 0.45 -1.1 -0.23 -0.7 1.3 -0.033 -1.3 -0.046 -0.47 8.3e+03 0.0037 45 1.2 ++
8 -1.2 1.2 0.45 0.52 -1.1 -0.22 -0.7 1.2 -0.0091 -1.3 -0.041 -0.47 8.3e+03 0.002 4.5e+02 1.2 ++
9 -1.3 1.2 0.49 0.56 -1.1 -0.2 -0.7 1.1 0.0013 -1.3 -0.038 -0.47 8.3e+03 0.00045 4.5e+03 1.1 ++
10 -1.3 1.3 0.5 0.57 -1.1 -0.2 -0.7 1.1 0.0047 -1.3 -0.037 -0.47 8.3e+03 4.6e-05 4.5e+04 1.1 ++
11 -1.3 1.3 0.5 0.57 -1.1 -0.2 -0.7 1.1 0.0047 -1.3 -0.037 -0.47 8.3e+03 3.2e-07 4.5e+04 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000109
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 -0.89 -
1 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 5 1 ++
2 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 2.5 1 -
3 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 1.2 1 -
4 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.62 1 -
5 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.31 1 -
6 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.16 1 -
7 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.078 1 -
8 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.039 1 -
9 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.02 -4.3 -
10 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.0098 -4.6 -
11 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.0049 -3.6 -
12 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.0024 -2.5 -
13 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.0012 -1.8 -
14 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.00061 -1 -
15 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.00031 -0.23 -
16 -0.5 -0.42 -0.016 -0.5 0.00031 -0.00031 -0.11 1.5 0.022 -0.018 -0.0056 9e+03 4.7 0.00031 0.57 +
17 -0.5 -0.42 -0.016 -0.5 0.00061 -0.00018 -0.12 1.5 0.022 -0.018 -0.0056 9e+03 4.8 0.00031 0.32 +
18 -0.5 -0.42 -0.016 -0.5 0.00092 -0.00027 -0.12 1.5 0.022 -0.019 -0.0057 9e+03 2.3 0.00031 0.68 +
19 -0.5 -0.42 -0.016 -0.5 0.0012 -0.00024 -0.12 1.5 0.022 -0.019 -0.0057 9e+03 0.38 0.0031 0.96 ++
20 -0.5 -0.42 -0.016 -0.5 0.0043 -0.00025 -0.12 1.5 0.021 -0.021 -0.0058 9e+03 0.072 0.031 1 ++
21 -0.5 -0.4 -0.016 -0.53 0.035 -0.00038 -0.14 1.5 0.0081 -0.038 -0.0067 8.9e+03 0.17 0.31 1 ++
22 -0.45 -0.16 -0.012 -0.7 0.17 -0.00096 -0.45 1.6 -0.029 -0.17 -0.018 8.6e+03 1.9 3.1 0.93 ++
23 -0.45 -0.16 -0.012 -0.7 0.17 -0.00096 -0.45 1.6 -0.029 -0.17 -0.018 8.6e+03 1.9 1.5 0.93 -
24 -0.45 -0.16 -0.012 -0.7 0.17 -0.00096 -0.45 1.6 -0.029 -0.17 -0.018 8.6e+03 1.9 0.76 -32 -
25 -0.45 -0.16 -0.012 -0.7 0.17 -0.00096 -0.45 1.6 -0.029 -0.17 -0.018 8.6e+03 1.9 0.38 -2.2 -
26 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.38 0.59 +
27 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.19 0.59 -
28 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.095 0.59 -
29 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.048 0.59 -
30 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.024 0.59 -
31 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.012 0.59 -
32 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.006 0.59 -
33 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.003 -2.4 -
34 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.0015 -2 -
35 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.00075 -1.5 -
36 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.00037 -0.81 -
37 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.00019 -0.044 -
38 -0.56 0.22 0.007 -0.93 -0.032 -0.00013 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 7.4 0.00019 0.77 +
39 -0.56 0.22 0.007 -0.93 -0.032 -9.8e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 6.3 0.00019 0.5 +
40 -0.56 0.22 0.007 -0.93 -0.032 -0.00011 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 0.073 0.0019 0.99 ++
41 -0.56 0.22 0.0071 -0.93 -0.03 -0.00012 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 0.15 0.019 1 ++
42 -0.56 0.22 0.0076 -0.94 -0.011 -0.0002 -0.78 1.8 0.18 -0.2 -0.053 8.5e+03 0.11 0.19 1 ++
43 -0.59 0.27 0.036 -1.1 -0.057 -6.3e-06 -0.6 1.9 0.076 -0.17 -0.088 8.4e+03 1.7 1.9 1 ++
44 -0.59 0.27 0.036 -1.1 -0.057 -6.3e-06 -0.6 1.9 0.076 -0.17 -0.088 8.4e+03 1.7 0.34 -2 -
45 -0.56 0.46 0.11 -1.5 -0.1 0.00017 -0.66 2.1 0.11 -0.024 -0.17 8.4e+03 15 0.34 0.86 +
46 -0.52 0.48 0.36 -1.6 -0.096 0.00016 -0.62 2.1 0.14 -0.032 -0.41 8.3e+03 4.1 3.4 0.97 ++
47 -0.55 0.51 0.34 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.03 -0.44 8.3e+03 0.022 34 0.99 ++
48 -0.56 0.51 0.34 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.45 8.3e+03 8.2e-05 3.4e+02 1 ++
49 -0.55 0.51 0.33 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.46 8.3e+03 6.7e-05 3.4e+03 1 ++
50 -0.55 0.51 0.33 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.46 8.3e+03 8.2e-06 3.4e+04 1 ++
51 -0.55 0.51 0.33 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.46 8.3e+03 6.3e-06 3.4e+05 1 ++
52 -0.55 0.51 0.33 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.46 8.3e+03 9.3e-07 3.4e+05 1 ++
Considering neighbor 1/20 for current solution
Attempt 93/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000110
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time lambda_travel_t b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 -0.45 0.2 -0.00013 -0.0098 -1 1.3 -0.35 -0.25 -0.17 -0.24 -0.23 -0.02 -0.25 8.9e+03 0.063 10 0.93 ++
1 -0.19 1.2 0.28 0.22 -2.7 -0.47 -0.95 -0.79 0.0057 -0.68 -0.13 -0.48 -0.09 8.8e+03 0.11 10 0.12 +
2 -0.19 1.2 0.28 0.22 -2.7 -0.47 -0.95 -0.79 0.0057 -0.68 -0.13 -0.48 -0.09 8.8e+03 0.11 1.7 -1.9 -
3 -0.98 1.2 0.48 0.34 -0.96 -0.54 -1.2 -0.54 0.54 -0.99 -0.019 -0.52 -1.1 8.4e+03 0.024 1.7 0.72 +
4 -0.98 1.2 0.48 0.34 -0.96 -0.54 -1.2 -0.54 0.54 -0.99 -0.019 -0.52 -1.1 8.4e+03 0.024 0.86 -0.68 -
5 -1.1 1.2 0.49 0.36 -1.7 0.31 -1.2 -0.95 0.15 -1.1 -0.27 -0.53 -0.85 8.2e+03 0.013 0.86 0.85 +
6 -0.93 1.2 0.55 0.56 -1.7 0.38 -1.1 -0.73 -0.051 -1 -0.071 -0.47 -0.43 8.2e+03 0.001 8.6 0.96 ++
7 -0.94 1.2 0.55 0.54 -1.7 0.38 -1.1 -0.75 -0.041 -1 -0.077 -0.48 -0.46 8.2e+03 7.5e-06 86 1 ++
8 -0.94 1.2 0.55 0.54 -1.7 0.38 -1.1 -0.75 -0.041 -1 -0.077 -0.48 -0.46 8.2e+03 3.1e-09 86 1 ++
Considering neighbor 0/20 for current solution
Attempt 94/100
Biogeme parameters read from biogeme.toml.
Model with 19 unknown parameters [max: 50]
*** Estimate b07everything_000111
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 9.3e+03 0.2 1 0.61 +
1 9.3e+03 0.2 0.5 -1.5 -
2 9.3e+03 0.2 0.25 -0.15 -
3 8.4e+03 0.05 0.25 0.84 +
4 8.3e+03 0.012 2.5 1.1 ++
5 8.3e+03 0.012 1.2 -7.2 -
6 8.2e+03 0.061 1.2 0.12 +
7 8.1e+03 0.0043 12 1 ++
8 8.1e+03 0.0037 1.2e+02 0.94 ++
9 8.1e+03 3.6e-05 1.2e+03 1 ++
10 8.1e+03 1.2e-08 1.2e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000112
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_com lambda_travel_t b_cost_train mu_existing asc_car b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.63 -1 -0.072 1.4 -0.55 1.9 0.24 0.12 -0.66 1e+04 0.24 1 0.37 +
1 -0.63 -1 -0.072 1.4 -0.55 1.9 0.24 0.12 -0.66 1e+04 0.24 0.5 -0.9 -
2 -0.26 -0.85 -0.0027 1.1 -0.43 1.8 -0.26 -0.29 -0.46 8.7e+03 0.097 0.5 0.75 +
3 -0.19 -0.87 0.078 0.68 -0.93 2.2 -0.32 -0.23 -0.54 8.4e+03 0.02 5 0.98 ++
4 0.23 -1.4 -0.39 0.14 -1.3 1.7 -0.079 -0.33 -0.59 8.3e+03 0.0077 5 0.81 +
5 0.29 -1.5 -0.34 0.39 -1.4 1.7 -0.069 -0.36 -0.64 8.3e+03 0.0039 5 0.87 +
6 0.27 -1.5 -0.33 0.36 -1.4 1.7 -0.073 -0.37 -0.64 8.3e+03 0.00012 50 1 ++
7 0.27 -1.5 -0.33 0.36 -1.4 1.7 -0.073 -0.37 -0.64 8.3e+03 3.1e-07 50 1 ++
Considering neighbor 1/20 for current solution
Attempt 95/100
Considering neighbor 0/20 for current solution
Attempt 96/100
Considering neighbor 0/20 for current solution
Attempt 97/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000113
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost mu_public asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 -0.68 -
1 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 5 1.1 ++
2 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 2.5 1.1 -
3 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 1.2 1.1 -
4 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.62 1.1 -
5 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.31 1.1 -
6 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.16 -2.9 -
7 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.078 -2.9 -
8 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.039 -3.2 -
9 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.02 -3.7 -
10 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0098 -4.2 -
11 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0049 -3.6 -
12 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0024 -2.5 -
13 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0012 -1.7 -
14 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00061 -0.96 -
15 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00031 -0.12 -
16 -0.5 -0.00028 -0.5 -0.02 -0.5 -0.16 0.00031 -0.00031 -0.14 1 0.026 -0.078 -0.022 -0.0066 9.2e+03 3.8 0.00031 0.68 +
17 -0.5 -0.00019 -0.5 -0.02 -0.5 -0.16 0.00061 -0.00021 -0.14 1 0.026 -0.078 -0.022 -0.0066 9.2e+03 4 0.00031 0.36 +
18 -0.5 -0.0001 -0.5 -0.02 -0.5 -0.16 0.00092 -0.00028 -0.14 1 0.026 -0.078 -0.022 -0.0066 9.2e+03 1.8 0.00031 0.76 +
19 -0.5 -1.1e-05 -0.5 -0.02 -0.5 -0.16 0.0012 -0.00026 -0.14 1 0.026 -0.078 -0.022 -0.0066 9.2e+03 0.26 0.0031 0.98 ++
20 -0.5 0.00091 -0.5 -0.02 -0.5 -0.16 0.0043 -0.00027 -0.14 1 0.025 -0.079 -0.023 -0.0067 9.2e+03 0.11 0.031 1 ++
21 -0.51 0.01 -0.49 -0.02 -0.53 -0.17 0.035 -0.0004 -0.15 1 0.018 -0.084 -0.031 -0.0072 9.1e+03 0.1 0.31 1 ++
22 -0.53 0.25 -0.29 -0.019 -0.82 -0.18 0.22 -0.0012 -0.45 1 -0.011 -0.2 -0.12 -0.017 8.8e+03 1.7 0.31 0.79 +
23 -0.62 0.55 -0.072 -0.015 -0.92 -0.16 -0.036 -0.0001 -0.69 1.3 0.1 -0.32 -0.11 -0.029 8.5e+03 0.41 0.31 0.71 +
24 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 3.1 0.96 ++
25 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 1.5 -1e+02 -
26 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 0.76 -34 -
27 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 0.38 -6.1 -
28 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 0.19 -0.68 -
29 -0.73 0.99 0.21 0.033 -1.4 -0.31 -0.11 0.00019 -0.72 1.6 -0.025 -0.51 -0.14 -0.071 8.2e+03 24 0.19 0.61 +
30 -0.7 1 0.28 0.088 -1.6 -0.46 -0.095 0.00017 -0.74 1.5 -0.038 -0.62 -0.11 -0.1 8.2e+03 14 0.19 0.86 +
31 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.19 0.34 +
32 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.095 -0.86 -
33 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.048 -0.62 -
34 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.024 -0.46 -
35 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.012 -0.64 -
36 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.006 -0.5 -
37 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.003 -0.37 -
38 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.0015 -0.33 -
39 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.00075 -0.31 -
40 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.00037 -0.31 -
41 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.00019 -0.3 -
42 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 9.3e-05 -0.3 -
43 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 4.7e-05 0.072 -
44 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 0.00012 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 0.78 4.7e-05 0.84 +
45 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 0.00012 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 0.024 0.00047 1 ++
46 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.089 0.00012 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 0.4 0.0047 1 ++
47 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.093 0.00014 -0.74 1.3 0.099 -0.79 -0.044 -0.15 8.2e+03 0.38 0.047 0.97 ++
48 -0.77 1.1 0.29 0.19 -1.7 -0.66 -0.1 0.00018 -0.72 1.3 0.067 -0.8 -0.069 -0.16 8.2e+03 1.3 0.47 0.98 ++
49 -1.1 1.3 0.43 0.4 -2 -1 -0.11 0.00021 -0.72 1 0.21 -1.2 -0.084 -0.32 8.2e+03 1.3 0.47 0.88 +
50 -1.3 1.5 0.51 0.47 -2 -1.1 -0.11 0.0002 -0.7 1 0.19 -1.2 -0.053 -0.4 8.1e+03 0.16 4.7 1 ++
51 -1.3 1.5 0.55 0.59 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.069 -0.49 8.1e+03 0.027 47 1 ++
52 -1.3 1.5 0.55 0.59 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.067 -0.52 8.1e+03 0.00073 4.7e+02 1 ++
53 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.067 -0.52 8.1e+03 0.0004 4.7e+03 1 ++
54 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.067 -0.52 8.1e+03 1.4e-05 4.7e+04 1 ++
55 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.067 -0.52 8.1e+03 4.6e-07 4.7e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 98/100
Considering neighbor 0/20 for current solution
Attempt 99/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000114
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train b_cost b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho
0 -0.82 0.19 0.025 -0.91 -0.67 -1 -0.3 -0.22 -0.067 -0.78 8.7e+03 0.078 10 1.1 ++
1 -0.92 0.71 0.68 -1.5 -0.77 -1.4 -0.5 -0.066 -0.41 -0.98 8.5e+03 0.028 1e+02 1.1 ++
2 -0.92 0.9 0.85 -1.7 -0.79 -1.5 -0.51 -0.072 -0.47 -1 8.5e+03 0.0035 1e+03 1.1 ++
3 -0.92 0.92 0.87 -1.7 -0.79 -1.5 -0.51 -0.073 -0.47 -1 8.5e+03 5.2e-05 1e+04 1 ++
4 -0.92 0.92 0.87 -1.7 -0.79 -1.5 -0.51 -0.073 -0.47 -1 8.5e+03 1.3e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Pareto file has been updated: b07everything_assisted.pareto
Before the algorithm: 431 models, with 14 Pareto.
After the algorithm: 466 models, with 14 Pareto.
VNS algorithm completed. Postprocessing of the Pareto optimal solutions
Pareto set initialized from file with 432 elements [14 Pareto] and 1 invalid elements.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000000.iter
Cannot read file __b07everything_000000.iter. Statement is ignored.
Starting values for the algorithm: {}
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.56 -
1 1e+04 1.5 0.5 0.2 +
2 1e+04 1.5 0.25 0.2 -
3 1e+04 1.5 0.12 0.2 -
4 1e+04 1.5 0.062 -4.2 -
5 9.9e+03 7.1 0.062 0.48 +
6 9.9e+03 7.1 0.031 0.0017 -
7 9.6e+03 1.2 0.031 0.12 +
8 9.6e+03 1.2 0.016 -0.32 -
9 9.3e+03 0.58 0.16 0.92 ++
10 9.3e+03 0.58 0.078 0.92 -
11 9.3e+03 0.58 0.039 -15 -
12 9.3e+03 0.58 0.02 -16 -
13 9.3e+03 0.58 0.0098 -6.7 -
14 9.3e+03 3.5 0.0098 0.56 +
15 9.3e+03 0.11 0.0098 0.88 +
16 9.2e+03 0.44 0.098 0.97 ++
17 9.1e+03 0.41 0.98 1 ++
18 9.1e+03 0.41 0.49 -0.77 -
19 8.7e+03 10 0.49 0.45 +
20 8.7e+03 10 0.24 0.45 -
21 8.7e+03 10 0.12 0.45 -
22 8.7e+03 10 0.061 0.45 -
23 8.7e+03 10 0.031 0.45 -
24 8.7e+03 10 0.015 0.45 -
25 8.7e+03 10 0.0076 0.45 -
26 8.7e+03 10 0.0038 -1.7 -
27 8.7e+03 10 0.0019 -1.1 -
28 8.7e+03 10 0.00095 -0.63 -
29 8.7e+03 10 0.00048 -0.36 -
30 8.7e+03 10 0.00024 -0.065 -
31 8.7e+03 6.6 0.00024 0.51 +
32 8.7e+03 7.8 0.00024 0.3 +
33 8.7e+03 1.4 0.00024 0.85 +
34 8.7e+03 0.19 0.0024 1 ++
35 8.7e+03 1.2 0.024 1 ++
36 8.6e+03 0.16 0.24 1 ++
37 8.3e+03 0.89 0.24 0.62 +
38 8.2e+03 0.22 2.4 0.98 ++
39 8.1e+03 0.091 24 1.1 ++
40 8.1e+03 0.77 24 0.75 +
41 8e+03 0.5 2.4e+02 1.1 ++
42 8e+03 0.5 1.2e+02 1.1 -
43 8e+03 0.5 60 1.1 -
44 8e+03 0.5 30 1.1 -
45 8e+03 0.5 15 1.1 -
46 8e+03 0.5 7.5 1.1 -
47 8e+03 0.5 3.7 1.1 -
48 8e+03 0.5 1.9 -4.9e+02 -
49 8e+03 0.5 0.93 -2e+02 -
50 8e+03 0.5 0.47 -19 -
51 8e+03 0.5 0.23 -1.2 -
52 8e+03 2.4 0.23 0.72 +
53 8e+03 3.2 2.3 1 ++
54 8e+03 3.2 0.39 -3.9 -
55 8e+03 2.4 0.39 0.47 +
56 8e+03 8.4 3.9 0.94 ++
57 8e+03 0.1 39 1 ++
58 8e+03 0.00059 3.9e+02 1 ++
59 8e+03 9.3e-06 3.9e+03 1 ++
60 8e+03 3.1e-06 3.9e+03 1 ++
Optimization algorithm has converged.
Relative gradient: 3.120917028152968e-06
Cause of termination: Relative gradient = 3.1e-06 <= 6.1e-06
Number of function evaluations: 118
Number of gradient evaluations: 57
Number of hessian evaluations: 28
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 61
Proportion of Hessian calculation: 28/28 = 100.0%
Optimization time: 0:00:07.554105
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000001.iter
Cannot read file __b07everything_000001.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 1 0.62 +
1 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 0.5 -0.081 -
2 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 5 0.9 ++
3 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 2.5 -1e+02 -
4 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 1.2 -5.7 -
5 -0.39 1.1 -1.2 -0.68 0.18 -0.6 2.1 0.016 -0.38 -0.66 -0.79 -1.3 -0.69 8.1e+03 0.018 1.2 0.71 +
6 -0.35 1.2 -1.7 -0.75 0.2 -0.73 1.4 0.14 -0.59 -0.95 -0.82 -1.5 -0.26 8.1e+03 0.011 1.2 0.73 +
7 -0.3 1.1 -1.8 -0.72 0.16 -0.72 1.6 0.14 -0.43 -0.95 -0.81 -1.5 -0.25 8.1e+03 0.0012 12 1.1 ++
8 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.39 -0.93 -0.79 -1.5 -0.25 8.1e+03 0.00084 1.2e+02 1.1 ++
9 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 2.3e-05 1.2e+03 1 ++
10 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 3.1e-08 1.2e+03 1 ++
Optimization algorithm has converged.
Relative gradient: 3.064634858623666e-08
Cause of termination: Relative gradient = 3.1e-08 <= 6.1e-06
Number of function evaluations: 28
Number of gradient evaluations: 17
Number of hessian evaluations: 8
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 11
Proportion of Hessian calculation: 8/8 = 100.0%
Optimization time: 0:00:04.660505
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000002.iter
Cannot read file __b07everything_000002.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car b_time_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.4 0.5 -0.21 -
1 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.5 0.88 +
2 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.25 0.88 -
3 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.12 0.88 -
4 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.062 0.88 -
5 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.031 -14 -
6 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.016 -6.7 -
7 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.0078 -2.8 -
8 -0.27 0.0077 -0.51 -0.0071 -0.00063 -0.046 1.2 -0.0003 -0.03 -0.028 0.19 9.3e+03 0.28 0.0078 0.86 +
9 -0.27 0.011 -0.51 -0.0047 -0.0004 -0.053 1.2 -0.0041 -0.032 -0.036 0.19 9.3e+03 0.071 0.078 1 ++
10 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.78 0.95 ++
11 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.39 0.95 -
12 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.2 -1.8 -
13 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.098 -0.87 -
14 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.049 -0.57 -
15 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.024 -0.59 -
16 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.012 -0.86 -
17 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.0061 -1.3 -
18 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.0031 -1.9 -
19 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.0015 -2.5 -
20 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.00076 -0.41 -
21 -0.28 0.044 -0.54 0.02 -0.00056 -0.12 1.2 -0.041 -0.057 -0.11 0.19 9.1e+03 0.81 0.00076 0.57 +
22 -0.28 0.045 -0.54 0.02 -0.00032 -0.12 1.2 -0.041 -0.057 -0.12 0.19 9.1e+03 0.17 0.0076 0.93 ++
23 -0.28 0.049 -0.54 0.021 -0.00037 -0.13 1.2 -0.042 -0.06 -0.12 0.18 9.1e+03 0.067 0.076 1 ++
24 -0.29 0.089 -0.56 0.035 -0.00033 -0.2 1.3 -0.051 -0.086 -0.16 0.13 9e+03 0.41 0.76 1 ++
25 -0.29 0.56 -0.75 0.22 -0.0012 -0.97 1.8 -0.13 -0.37 -0.53 -0.55 8.4e+03 4.6 0.76 0.71 +
26 -0.29 0.56 -0.75 0.22 -0.0012 -0.97 1.8 -0.13 -0.37 -0.53 -0.55 8.4e+03 4.6 0.38 -9 -
27 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.38 0.87 +
28 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.19 -0.12 -
29 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.095 0.0036 -
30 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.048 -0.045 -
31 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.024 -0.031 -
32 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.012 -0.13 -
33 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.006 -0.21 -
34 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.003 -0.34 -
35 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.0015 -0.45 -
36 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.00075 -0.52 -
37 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.00037 -0.56 -
38 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.00019 -0.55 -
39 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 9.3e-05 0.082 -
40 -0.37 0.66 -0.81 0.079 -0.00057 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 0.99 9.3e-05 0.63 +
41 -0.37 0.66 -0.81 0.079 -0.00056 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 0.08 0.00093 0.98 ++
42 -0.37 0.66 -0.81 0.08 -0.00057 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 0.022 0.0093 1 ++
43 -0.38 0.66 -0.82 0.089 -0.0006 -0.58 1.8 -0.21 -0.4 -0.54 -0.64 8.3e+03 0.049 0.093 1 ++
44 -0.42 0.73 -0.86 0.091 -0.00061 -0.58 1.8 -0.25 -0.43 -0.61 -0.74 8.3e+03 0.025 0.93 1 ++
45 -0.42 0.73 -0.86 0.091 -0.00061 -0.58 1.8 -0.25 -0.43 -0.61 -0.74 8.3e+03 0.025 0.47 -15 -
46 -0.42 0.73 -0.86 0.091 -0.00061 -0.58 1.8 -0.25 -0.43 -0.61 -0.74 8.3e+03 0.025 0.23 -7.5 -
47 -0.42 0.73 -0.86 0.091 -0.00061 -0.58 1.8 -0.25 -0.43 -0.61 -0.74 8.3e+03 0.025 0.12 0.009 -
48 -0.48 0.8 -0.93 -0.021 -0.00015 -0.56 1.9 -0.29 -0.46 -0.67 -0.85 8.2e+03 0.23 0.12 0.65 +
49 -0.5 0.83 -1 0.0093 -0.00028 -0.55 1.9 -0.32 -0.46 -0.75 -0.97 8.2e+03 0.069 1.2 0.98 ++
50 -0.5 0.83 -1 0.0093 -0.00028 -0.55 1.9 -0.32 -0.46 -0.75 -0.97 8.2e+03 0.069 0.58 -26 -
51 -0.5 0.83 -1 0.0093 -0.00028 -0.55 1.9 -0.32 -0.46 -0.75 -0.97 8.2e+03 0.069 0.29 -11 -
52 -0.5 0.83 -1 0.0093 -0.00028 -0.55 1.9 -0.32 -0.46 -0.75 -0.97 8.2e+03 0.069 0.15 -3.7 -
53 -0.54 0.85 -1.1 -0.077 7.7e-05 -0.54 2 -0.37 -0.45 -0.84 -1.1 8.2e+03 3.8 0.15 0.54 +
54 -0.52 0.87 -1.2 -0.049 -4.4e-05 -0.55 2 -0.37 -0.44 -0.88 -1.3 8.2e+03 2.3 1.5 1 ++
55 -0.52 0.87 -1.2 -0.049 -4.4e-05 -0.55 2 -0.37 -0.44 -0.88 -1.3 8.2e+03 2.3 0.54 -7.2 -
56 -0.52 0.87 -1.2 -0.049 -4.4e-05 -0.55 2 -0.37 -0.44 -0.88 -1.3 8.2e+03 2.3 0.27 -0.083 -
57 -0.52 0.88 -1.5 -0.099 0.00018 -0.55 2 -0.45 -0.39 -1.1 -1.5 8.1e+03 4.6 0.27 0.86 +
58 -0.44 0.91 -1.7 -0.092 0.00014 -0.57 2.1 -0.46 -0.34 -1.2 -1.8 8.1e+03 0.68 2.7 0.98 ++
59 -0.32 0.98 -2.1 -0.11 0.00024 -0.6 1.9 -0.47 -0.3 -1.5 -2.2 8.1e+03 11 2.7 0.7 +
60 -0.3 1 -2.2 -0.11 0.00021 -0.62 1.8 -0.46 -0.36 -1.5 -2.2 8.1e+03 0.43 27 1 ++
61 -0.31 1 -2.2 -0.11 0.00021 -0.62 1.8 -0.47 -0.37 -1.5 -2.2 8.1e+03 0.032 2.7e+02 1 ++
62 -0.31 1 -2.1 -0.11 0.00021 -0.62 1.8 -0.47 -0.37 -1.5 -2.2 8.1e+03 5.3e-05 2.7e+03 1 ++
63 -0.31 1 -2.1 -0.11 0.00021 -0.62 1.8 -0.47 -0.37 -1.5 -2.2 8.1e+03 2.1e-07 2.7e+03 1 ++
Optimization algorithm has converged.
Relative gradient: 2.057302293522673e-07
Cause of termination: Relative gradient = 2.1e-07 <= 6.1e-06
Number of function evaluations: 117
Number of gradient evaluations: 53
Number of hessian evaluations: 26
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 64
Proportion of Hessian calculation: 26/26 = 100.0%
Optimization time: 0:00:03.318545
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000003.iter
Cannot read file __b07everything_000003.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.85 0.43 -0.99 1.8 -1 1.6 0.36 -0.32 9.1e+03 0.1 1 0.54 +
1 -0.39 1.1 -0.78 1 -2.2e-16 2.6 -0.27 -0.52 8.8e+03 0.15 1 0.28 +
2 -0.15 0.13 -1.1 0.1 -0.35 3.5 0.19 0.11 8.6e+03 0.093 1 0.28 +
3 -0.15 0.13 -1.1 0.1 -0.35 3.5 0.19 0.11 8.6e+03 0.093 0.5 0.057 -
4 -0.16 0.63 -1 0.21 -0.44 3.5 0.11 -0.29 8.3e+03 0.023 0.5 0.85 +
5 -0.27 0.69 -0.97 0.34 -0.33 3 0.058 -0.22 8.3e+03 0.013 5 1 ++
6 -0.27 0.69 -0.97 0.34 -0.33 3 0.058 -0.22 8.3e+03 0.013 1 -1.5 -
7 -0.23 1 -1.4 0.23 -0.51 2 0.22 -0.37 8.2e+03 0.019 10 1 ++
8 -0.43 1.1 -1.5 0.33 -0.59 1.6 0.17 -0.55 8.2e+03 0.006 1e+02 1.1 ++
9 -0.5 1.2 -1.5 0.33 -0.6 1.6 0.18 -0.62 8.2e+03 0.00046 1e+03 1.1 ++
10 -0.51 1.2 -1.5 0.33 -0.61 1.6 0.18 -0.64 8.2e+03 1.8e-05 1e+04 1 ++
11 -0.51 1.2 -1.5 0.33 -0.61 1.6 0.18 -0.64 8.2e+03 2.8e-09 1e+04 1 ++
Optimization algorithm has converged.
Relative gradient: 2.7525581335143016e-09
Cause of termination: Relative gradient = 2.8e-09 <= 6.1e-06
Number of function evaluations: 33
Number of gradient evaluations: 21
Number of hessian evaluations: 10
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 12
Proportion of Hessian calculation: 10/10 = 100.0%
Optimization time: 0:00:04.368402
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000004.iter
Cannot read file __b07everything_000004.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.26 -
1 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.5 0.85 +
2 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.25 0.85 -
3 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.12 0.85 -
4 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.062 0.85 -
5 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.031 -32 -
6 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.016 -7.4 -
7 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.0078 -2.2 -
8 -0.27 0.0077 -0.51 -0.079 -0.007 0.00013 -0.046 1.2 -0.0003 -0.03 -0.028 -0.014 0.19 0.054 9.3e+03 0.31 0.078 0.94 ++
9 -0.27 0.039 -0.53 -0.086 0.016 -0.0016 -0.11 1.2 -0.036 -0.053 -0.11 -0.039 0.19 0.067 9.2e+03 6 0.078 0.68 +
10 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.078 0.62 +
11 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.039 0.62 -
12 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.02 0.62 -
13 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0098 -6.1 -
14 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0049 -4 -
15 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0024 -2.3 -
16 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0012 -0.28 -
17 -0.28 0.081 -0.56 -0.099 0.0014 -0.00019 -0.19 1.3 -0.045 -0.08 -0.16 -0.079 0.14 0.082 9e+03 1.1 0.012 0.96 ++
18 -0.28 0.088 -0.57 -0.1 0.0068 -0.00029 -0.2 1.3 -0.045 -0.085 -0.17 -0.082 0.13 0.083 9e+03 0.32 0.12 0.99 ++
19 -0.28 0.16 -0.61 -0.11 0.057 -0.00047 -0.32 1.4 -0.045 -0.13 -0.2 -0.11 0.028 0.099 8.8e+03 0.23 1.2 0.99 ++
20 -0.28 0.16 -0.61 -0.11 0.057 -0.00047 -0.32 1.4 -0.045 -0.13 -0.2 -0.11 0.028 0.099 8.8e+03 0.23 0.61 -0.95 -
21 -0.18 0.54 -0.57 -0.16 0.24 -0.0012 -0.76 1.7 -0.15 -0.34 -0.56 -0.24 -0.58 0.16 8.6e+03 1.6 0.61 0.29 +
22 -0.18 0.54 -0.57 -0.16 0.24 -0.0012 -0.76 1.7 -0.15 -0.34 -0.56 -0.24 -0.58 0.16 8.6e+03 1.6 0.31 -0.7 -
23 -0.31 0.64 -0.58 -0.22 0.48 -0.0021 -0.58 2 -0.17 -0.38 -0.35 -0.16 -0.67 0.34 8.4e+03 6.9 0.31 0.55 +
24 -0.46 0.75 -0.52 -0.094 0.34 -0.0016 -0.53 2 -0.34 -0.43 -0.34 0.032 -0.57 0.65 8.2e+03 1.4 0.31 0.88 +
25 -0.76 0.89 -0.58 0.061 0.3 -0.0014 -0.57 1.9 -0.5 -0.44 -0.43 0.15 -0.82 0.7 8.1e+03 0.89 3.1 0.96 ++
26 -0.76 0.89 -0.58 0.061 0.3 -0.0014 -0.57 1.9 -0.5 -0.44 -0.43 0.15 -0.82 0.7 8.1e+03 0.89 0.71 -1.2e+02 -
27 -0.76 0.89 -0.58 0.061 0.3 -0.0014 -0.57 1.9 -0.5 -0.44 -0.43 0.15 -0.82 0.7 8.1e+03 0.89 0.36 -15 -
28 -0.77 1.1 -0.84 0.24 0.093 -0.00059 -0.6 1.7 -0.46 -0.36 -0.64 0.34 -1.1 1.1 8.1e+03 0.67 0.36 0.64 +
29 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 3.6 1.2 ++
30 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 0.77 -1.8e+02 -
31 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 0.38 -20 -
32 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 0.19 -0.21 -
33 -0.69 1.1 -1.3 0.21 -0.028 -0.0001 -0.61 1.8 -0.47 -0.37 -0.96 0.37 -1.5 1.3 8.1e+03 2.1 0.19 0.86 +
34 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 1.9 1 ++
35 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 0.96 -1.1e+02 -
36 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 0.48 -14 -
37 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 0.24 -1.7 -
38 -0.49 1.1 -1.7 0.17 -0.085 8.5e-05 -0.59 1.9 -0.44 -0.34 -1.3 0.34 -1.9 1.2 8.1e+03 13 0.24 0.73 +
39 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.24 0.56 +
40 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.12 -3.6 -
41 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.06 -2.9 -
42 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.03 -2.6 -
43 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.015 -2.5 -
44 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.0075 -2.5 -
45 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.0037 -2.1 -
46 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.0019 -2.1 -
47 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00094 -2.1 -
48 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00047 -2.1 -
49 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00023 -2.2 -
50 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00012 -2.2 -
51 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 5.9e-05 -1.4 -
52 -0.38 0.99 -1.9 0.17 -0.096 0.00014 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 19 5.9e-05 0.22 +
53 -0.38 0.99 -1.9 0.17 -0.096 0.00017 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 6.9 5.9e-05 0.74 +
54 -0.38 0.99 -1.9 0.17 -0.096 0.00016 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 1 5.9e-05 0.89 +
55 -0.38 0.99 -1.9 0.17 -0.096 0.00016 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 0.012 0.00059 1 ++
56 -0.38 0.99 -1.9 0.17 -0.095 0.00016 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 0.15 0.0059 1 ++
57 -0.38 0.99 -1.9 0.16 -0.094 0.00015 -0.59 1.9 -0.41 -0.29 -1.5 0.16 -2.1 1.1 8e+03 0.011 0.059 1 ++
58 -0.34 1 -2 0.12 -0.096 0.00016 -0.61 1.9 -0.42 -0.31 -1.5 0.18 -2.1 1.1 8e+03 0.13 0.59 1 ++
59 -0.29 1 -2.1 -0.1 -0.1 0.00019 -0.62 1.8 -0.39 -0.39 -1.6 -0.1 -2.2 0.72 8e+03 2.5 5.9 0.97 ++
60 -0.28 1 -2.1 -0.12 -0.1 0.00019 -0.62 1.8 -0.39 -0.35 -1.6 -0.12 -2.2 0.69 8e+03 0.046 59 1 ++
61 -0.28 1 -2.1 -0.13 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.14 -2.2 0.67 8e+03 0.00019 5.9e+02 1 ++
62 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.66 8e+03 0.00014 5.9e+03 1 ++
63 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.66 8e+03 0.00014 5.9e+04 1 ++
64 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.65 8e+03 3.3e-05 5.9e+05 1 ++
65 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.65 8e+03 5e-06 5.9e+05 1 ++
Optimization algorithm has converged.
Relative gradient: 5.0206033633660125e-06
Cause of termination: Relative gradient = 5e-06 <= 6.1e-06
Number of function evaluations: 129
Number of gradient evaluations: 63
Number of hessian evaluations: 31
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 66
Proportion of Hessian calculation: 31/31 = 100.0%
Optimization time: 0:00:06.056538
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000005.iter
Cannot read file __b07everything_000005.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time b_cost mu_existing asc_car Function Relgrad Radius Rho
0 -0.7 -0.85 -1 1.6 0.34 8.9e+03 0.12 1 0.79 +
1 -0.7 -0.85 -1 1.6 0.34 8.9e+03 0.12 0.5 -0.8 -
2 -0.39 -0.99 -0.5 1.9 -0.088 8.6e+03 0.031 0.5 0.78 +
3 -0.37 -0.93 -0.62 2.1 -0.0038 8.5e+03 0.0021 5 0.96 ++
4 -0.37 -0.96 -0.63 2 -0.00094 8.5e+03 0.00013 50 0.97 ++
5 -0.37 -0.96 -0.63 2 -0.00094 8.5e+03 6.7e-07 50 1 ++
Optimization algorithm has converged.
Relative gradient: 6.680761256997596e-07
Cause of termination: Relative gradient = 6.7e-07 <= 6.1e-06
Number of function evaluations: 17
Number of gradient evaluations: 11
Number of hessian evaluations: 5
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 6
Proportion of Hessian calculation: 5/5 = 100.0%
Optimization time: 0:00:01.213835
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000006.iter
Cannot read file __b07everything_000006.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 -2 -
1 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.25 -0.14 -
2 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 2.5 1 ++
3 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 1.2 1 -
4 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 0.62 1 -
5 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 0.31 -2.2 -
6 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 0.16 -0.79 -
7 -0.32 0.02 -0.41 -0.31 0.15 -0.0034 -0.33 1.3 0.24 -0.28 -0.035 0.21 9.1e+03 13 0.16 0.17 +
8 -0.32 0.02 -0.41 -0.31 0.15 -0.0034 -0.33 1.3 0.24 -0.28 -0.035 0.21 9.1e+03 13 0.078 -0.091 -
9 -0.32 0.02 -0.41 -0.31 0.15 -0.0034 -0.33 1.3 0.24 -0.28 -0.035 0.21 9.1e+03 13 0.039 0.06 -
10 -0.32 0.031 -0.44 -0.32 0.12 0.0022 -0.33 1.4 0.24 -0.29 -0.031 0.17 9e+03 6.4 0.039 0.14 +
11 -0.32 0.031 -0.44 -0.32 0.12 0.0022 -0.33 1.4 0.24 -0.29 -0.031 0.17 9e+03 6.4 0.02 0.14 -
12 -0.32 0.031 -0.44 -0.32 0.12 0.0022 -0.33 1.4 0.24 -0.29 -0.031 0.17 9e+03 6.4 0.0098 -2 -
13 -0.32 0.031 -0.44 -0.32 0.12 0.0022 -0.33 1.4 0.24 -0.29 -0.031 0.17 9e+03 6.4 0.0049 -1.2 -
14 -0.32 0.034 -0.44 -0.32 0.11 -0.0027 -0.34 1.4 0.24 -0.3 -0.031 0.17 8.9e+03 13 0.0049 0.1 +
15 -0.32 0.036 -0.44 -0.32 0.11 0.00098 -0.34 1.4 0.24 -0.3 -0.031 0.16 8.9e+03 6.3 0.0049 0.25 +
16 -0.32 0.036 -0.44 -0.32 0.11 0.00098 -0.34 1.4 0.24 -0.3 -0.031 0.16 8.9e+03 6.3 0.0024 -0.79 -
17 -0.31 0.038 -0.44 -0.32 0.1 -0.0015 -0.34 1.4 0.24 -0.3 -0.03 0.16 8.8e+03 7.3 0.0024 0.45 +
18 -0.31 0.038 -0.44 -0.32 0.1 -0.0015 -0.34 1.4 0.24 -0.3 -0.03 0.16 8.8e+03 7.3 0.0012 -0.014 -
19 -0.31 0.039 -0.44 -0.32 0.11 -0.00024 -0.34 1.4 0.23 -0.3 -0.029 0.16 8.8e+03 6.3 0.0012 0.23 +
20 -0.31 0.039 -0.44 -0.32 0.11 -0.00024 -0.34 1.4 0.23 -0.3 -0.029 0.16 8.8e+03 6.3 0.00061 -0.11 -
21 -0.31 0.04 -0.44 -0.32 0.11 -0.00085 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 3.5 0.00061 0.55 +
22 -0.31 0.04 -0.44 -0.32 0.11 -0.00085 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 3.5 0.00031 -1.1 -
23 -0.31 0.04 -0.44 -0.32 0.11 -0.00085 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 3.5 0.00015 -0.1 -
24 -0.31 0.04 -0.44 -0.32 0.11 -0.0007 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 0.6 0.00015 0.83 +
25 -0.31 0.04 -0.44 -0.32 0.11 -0.00069 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 0.07 0.0015 0.99 ++
26 -0.31 0.041 -0.44 -0.32 0.11 -0.00069 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 0.13 0.015 1 ++
27 -0.31 0.046 -0.45 -0.32 0.11 -0.00069 -0.34 1.4 0.23 -0.31 -0.028 0.14 8.7e+03 0.066 0.15 1 ++
28 -0.3 0.1 -0.49 -0.33 0.11 -0.00069 -0.37 1.4 0.21 -0.36 -0.032 -0.013 8.6e+03 0.09 1.5 0.99 ++
29 -0.55 1.1 -0.83 -0.54 -0.13 0.00031 -0.64 2 -0.36 -0.44 -0.23 -0.65 8.3e+03 18 1.5 0.56 +
30 -0.55 1.1 -0.83 -0.54 -0.13 0.00031 -0.64 2 -0.36 -0.44 -0.23 -0.65 8.3e+03 18 0.76 -1.8 -
31 -0.55 1.1 -0.83 -0.54 -0.13 0.00031 -0.64 2 -0.36 -0.44 -0.23 -0.65 8.3e+03 18 0.38 -0.049 -
32 -0.64 0.99 -1.2 -0.72 -0.062 -9.9e-06 -0.58 2 -0.34 -0.4 -0.24 -0.67 8.1e+03 12 0.38 0.65 +
33 -0.64 0.99 -1.2 -0.72 -0.062 -9.9e-06 -0.58 2 -0.34 -0.4 -0.24 -0.67 8.1e+03 12 0.19 -1.1 -
34 -0.64 0.99 -1.2 -0.72 -0.062 -9.9e-06 -0.58 2 -0.34 -0.4 -0.24 -0.67 8.1e+03 12 0.095 -0.098 -
35 -0.58 1 -1.3 -0.75 -0.12 0.00027 -0.56 2 -0.35 -0.38 -0.25 -0.68 8.1e+03 3.3 0.095 0.32 +
36 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.095 0.33 +
37 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.048 -1.1 -
38 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.024 -0.76 -
39 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.012 -0.56 -
40 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.006 -0.29 -
41 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.003 -0.19 -
42 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.0015 -0.15 -
43 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.00075 -0.13 -
44 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.00037 -0.12 -
45 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.00019 -0.12 -
46 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 9.3e-05 -0.12 -
47 -0.5 1 -1.4 -0.73 -0.092 0.00017 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 22 9.3e-05 0.49 +
48 -0.5 1 -1.4 -0.73 -0.092 0.00017 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 22 4.7e-05 -0.91 -
49 -0.51 1 -1.4 -0.73 -0.092 0.00012 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 20 4.7e-05 0.26 +
50 -0.51 1 -1.4 -0.73 -0.092 0.00015 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 13 4.7e-05 0.5 +
51 -0.51 1 -1.4 -0.73 -0.092 0.00013 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 3.6 4.7e-05 0.78 +
52 -0.51 1 -1.4 -0.73 -0.092 0.00014 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 0.084 0.00047 0.99 ++
53 -0.51 1 -1.4 -0.73 -0.092 0.00014 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 0.029 0.0047 1 ++
54 -0.51 1 -1.4 -0.73 -0.097 0.00016 -0.61 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 0.29 0.047 0.96 ++
55 -0.51 1 -1.4 -0.72 -0.1 0.00018 -0.63 1.9 -0.32 -0.35 -0.2 -0.69 8.1e+03 0.42 0.47 1 ++
56 -0.49 1.1 -1.7 -0.67 -0.1 0.00019 -0.77 1.5 -0.27 -0.48 -0.24 -0.74 8.1e+03 0.41 0.47 0.83 +
57 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.78 1.6 -0.27 -0.49 -0.24 -0.74 8.1e+03 0.041 4.7 1 ++
58 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.77 1.6 -0.27 -0.48 -0.24 -0.74 8.1e+03 0.0029 47 1 ++
59 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.77 1.6 -0.27 -0.48 -0.24 -0.74 8.1e+03 3e-05 4.7e+02 1 ++
60 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.77 1.6 -0.27 -0.48 -0.24 -0.74 8.1e+03 7.4e-05 4.7e+03 1 ++
61 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.77 1.6 -0.27 -0.48 -0.24 -0.74 8.1e+03 3.5e-07 4.7e+03 1 ++
Optimization algorithm has converged.
Relative gradient: 3.5364145945823094e-07
Cause of termination: Relative gradient = 3.5e-07 <= 6.1e-06
Number of function evaluations: 125
Number of gradient evaluations: 63
Number of hessian evaluations: 31
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 62
Proportion of Hessian calculation: 31/31 = 100.0%
Optimization time: 0:00:03.571153
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000007.iter
Cannot read file __b07everything_000007.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time b_cost asc_car Function Relgrad Radius Rho
0 -0.76 -0.77 -0.7 -0.29 8.8e+03 0.04 10 1.1 ++
1 -0.66 -1.2 -0.77 -0.0015 8.7e+03 0.0064 1e+02 1.1 ++
2 -0.65 -1.3 -0.79 0.016 8.7e+03 0.00012 1e+03 1 ++
3 -0.65 -1.3 -0.79 0.016 8.7e+03 4e-08 1e+03 1 ++
Optimization algorithm has converged.
Relative gradient: 3.954408093567457e-08
Cause of termination: Relative gradient = 4e-08 <= 6.1e-06
Number of function evaluations: 13
Number of gradient evaluations: 9
Number of hessian evaluations: 4
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 4
Proportion of Hessian calculation: 4/4 = 100.0%
Optimization time: 0:00:00.322616
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000008.iter
Cannot read file __b07everything_000008.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.84 0.39 -0.81 -0.5 1.9 -1 1.7 0.4 -0.3 9.3e+03 0.1 1 0.45 +
1 -0.59 0.95 -0.13 -0.46 1.6 0 2.5 -0.41 -0.45 9e+03 0.16 1 0.27 +
2 -0.57 0.24 -0.39 -0.27 0.85 -0.47 3.5 -0.12 -0.11 8.5e+03 0.066 1 0.61 +
3 -0.34 0.73 -1 -0.12 0.092 -0.46 2.5 0.084 -0.039 8.3e+03 0.013 10 1.1 ++
4 -0.44 1 -1.3 -0.44 0.47 -0.64 1.4 0.18 -0.26 8.2e+03 0.016 10 0.68 +
5 -0.56 1.2 -1.2 -0.51 0.35 -0.65 1.5 0.18 -0.64 8.2e+03 0.002 1e+02 1 ++
6 -0.56 1.2 -1.2 -0.52 0.35 -0.66 1.5 0.18 -0.69 8.2e+03 2.6e-05 1e+03 1 ++
7 -0.56 1.2 -1.2 -0.52 0.35 -0.66 1.5 0.18 -0.69 8.2e+03 2.3e-08 1e+03 1 ++
Optimization algorithm has converged.
Relative gradient: 2.2826880645845276e-08
Cause of termination: Relative gradient = 2.3e-08 <= 6.1e-06
Number of function evaluations: 25
Number of gradient evaluations: 17
Number of hessian evaluations: 8
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 8
Proportion of Hessian calculation: 8/8 = 100.0%
Optimization time: 0:00:04.672481
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000009.iter
Cannot read file __b07everything_000009.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.68 0.25 -1 1.5 -0.54 -0.26 -0.22 8.8e+03 0.044 1 0.86 +
1 -1.1 1.2 -1.3 0.78 -0.82 -0.027 -0.62 8.3e+03 0.014 10 1.1 ++
2 -0.83 1.7 -1.8 0.26 -0.72 0.22 -1.1 8.2e+03 0.007 10 0.87 +
3 -0.9 1.7 -1.7 0.35 -0.72 0.17 -1.2 8.2e+03 0.00063 1e+02 1.1 ++
4 -0.9 1.7 -1.7 0.37 -0.72 0.17 -1.2 8.2e+03 1.1e-05 1e+03 1 ++
5 -0.9 1.7 -1.7 0.37 -0.72 0.17 -1.2 8.2e+03 2e-09 1e+03 1 ++
Optimization algorithm has converged.
Relative gradient: 2.014992483365034e-09
Cause of termination: Relative gradient = 2e-09 <= 6.1e-06
Number of function evaluations: 19
Number of gradient evaluations: 13
Number of hessian evaluations: 6
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 6
Proportion of Hessian calculation: 6/6 = 100.0%
Optimization time: 0:00:01.139257
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000010.iter
Cannot read file __b07everything_000010.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car b_time_swissmet Function Relgrad Radius Rho
0 -0.95 0.41 -0.8 1.7 -1 1.8 -0.012 -0.34 -0.58 -0.63 8.8e+03 0.077 1 0.69 +
1 -0.95 0.41 -0.8 1.7 -1 1.8 -0.012 -0.34 -0.58 -0.63 8.8e+03 0.077 0.5 0.085 -
2 -0.65 0.69 -0.77 1.3 -0.5 1.9 -0.28 -0.39 -0.46 -0.79 8.3e+03 0.025 5 0.91 ++
3 -0.11 0.93 -1.8 -0.18 -0.57 2.1 0.19 -0.23 -1.3 -1.9 8.3e+03 0.078 5 0.18 +
4 -0.15 0.97 -2.1 -0.17 -0.58 2 0.095 -0.25 -1.3 -1.3 8.1e+03 0.0062 50 0.95 ++
5 -0.2 1 -2 0.19 -0.62 1.8 0.13 -0.35 -1.3 -1.6 8.1e+03 0.0024 5e+02 0.92 ++
6 -0.23 1 -2 0.16 -0.62 1.8 0.12 -0.35 -1.3 -1.6 8.1e+03 7.1e-05 5e+03 1 ++
7 -0.23 1 -2 0.16 -0.62 1.8 0.12 -0.35 -1.3 -1.6 8.1e+03 8.5e-08 5e+03 1 ++
Optimization algorithm has converged.
Relative gradient: 8.523728224989289e-08
Cause of termination: Relative gradient = 8.5e-08 <= 6.1e-06
Number of function evaluations: 23
Number of gradient evaluations: 15
Number of hessian evaluations: 7
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 8
Proportion of Hessian calculation: 7/7 = 100.0%
Optimization time: 0:00:06.163273
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000011.iter
Cannot read file __b07everything_000011.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.53 -
1 1e+04 1.4 0.5 0.28 +
2 1e+04 1.4 0.25 0.28 -
3 1e+04 1.4 0.12 0.28 -
4 1e+04 1.4 0.062 -5.6 -
5 1e+04 1.4 0.031 -0.69 -
6 9.5e+03 1.1 0.031 0.88 +
7 9.5e+03 1.1 0.016 -9.8 -
8 9.3e+03 0.71 0.16 0.94 ++
9 9.1e+03 0.66 1.6 1 ++
10 9.1e+03 0.66 0.78 -3.1 -
11 9.1e+03 0.66 0.39 -0.55 -
12 8.8e+03 8.3 0.39 0.43 +
13 8.8e+03 8.3 0.2 0.43 -
14 8.8e+03 8.3 0.098 0.43 -
15 8.8e+03 8.3 0.049 0.43 -
16 8.8e+03 8.3 0.024 0.43 -
17 8.8e+03 8.3 0.012 0.43 -
18 8.8e+03 8.3 0.0061 -2 -
19 8.8e+03 8.3 0.0031 -1.2 -
20 8.8e+03 8.3 0.0015 -0.12 -
21 8.7e+03 7.2 0.0015 0.87 +
22 8.7e+03 7.2 0.00076 -1.1 -
23 8.7e+03 7.2 0.00038 -1.1 -
24 8.7e+03 7.2 0.00019 -0.44 -
25 8.7e+03 7.5 0.00019 0.28 +
26 8.7e+03 7.5 9.5e-05 -0.12 -
27 8.7e+03 2.5 9.5e-05 0.58 +
28 8.7e+03 0.22 0.00095 0.98 ++
29 8.7e+03 0.29 0.0095 1 ++
30 8.6e+03 0.19 0.095 1 ++
31 8.4e+03 0.089 0.95 0.99 ++
32 8.4e+03 0.089 0.48 -2.7 -
33 8.3e+03 0.1 0.48 0.47 +
34 8.2e+03 0.2 0.48 0.79 +
35 8.1e+03 1.2 0.48 0.29 +
36 8.1e+03 0.034 0.48 0.9 +
37 8.1e+03 0.034 0.24 -5 -
38 8.1e+03 5 0.24 0.23 +
39 8.1e+03 5.7 2.4 0.94 ++
40 8.1e+03 5.7 0.56 -18 -
41 8.1e+03 5.7 0.28 -2.1 -
42 8e+03 9.5 0.28 0.59 +
43 8e+03 1.5 2.8 0.98 ++
44 8e+03 0.2 28 1 ++
45 8e+03 0.0087 2.8e+02 1 ++
46 8e+03 0.00034 2.8e+03 1 ++
47 8e+03 0.00039 2.8e+04 1 ++
48 8e+03 1.1e-05 2.8e+05 1 ++
49 8e+03 0.00055 2.8e+06 1 ++
50 8e+03 6.7e-07 2.8e+06 1 ++
Optimization algorithm has converged.
Relative gradient: 6.724715452618466e-07
Cause of termination: Relative gradient = 6.7e-07 <= 6.1e-06
Number of function evaluations: 106
Number of gradient evaluations: 55
Number of hessian evaluations: 27
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 51
Proportion of Hessian calculation: 27/27 = 100.0%
Optimization time: 0:00:04.895620
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000012.iter
Cannot read file __b07everything_000012.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.33 -
1 9.5e+03 1.1 0.5 0.7 +
2 9.5e+03 1.1 0.25 0.7 -
3 9.5e+03 1.1 0.12 0.7 -
4 9.5e+03 1.1 0.062 0.7 -
5 9.5e+03 1.1 0.031 -36 -
6 9.5e+03 1.1 0.016 -4 -
7 9.3e+03 3.9 0.016 0.77 +
8 9.3e+03 0.073 0.16 0.9 ++
9 9.1e+03 2.7 1.6 0.9 ++
10 9.1e+03 2.7 0.78 0.9 -
11 9.1e+03 2.7 0.39 0.9 -
12 9.1e+03 2.7 0.2 0.9 -
13 9.1e+03 2.7 0.098 0.9 -
14 9.1e+03 2.7 0.049 -5.8 -
15 9.1e+03 2.7 0.024 -6.3 -
16 9.1e+03 2.7 0.012 -6.8 -
17 9.1e+03 2.7 0.0061 -7.2 -
18 9.1e+03 2.7 0.0031 -4.1 -
19 9.1e+03 2.7 0.0015 -2.1 -
20 9.1e+03 2.7 0.00076 -0.59 -
21 9e+03 2.9 0.00076 0.32 +
22 9e+03 2.9 0.00038 -0.13 -
23 9e+03 1.4 0.00038 0.63 +
24 9e+03 0.31 0.0038 0.92 ++
25 9e+03 0.069 0.038 1 ++
26 9e+03 0.24 0.38 1 ++
27 8.7e+03 2.3 0.38 0.65 +
28 8.7e+03 2.3 0.19 -0.28 -
29 8.4e+03 5.9 0.19 0.86 +
30 8.4e+03 5.9 0.095 -0.41 -
31 8.4e+03 5.9 0.048 -0.4 -
32 8.4e+03 5.9 0.024 -0.66 -
33 8.4e+03 5.9 0.012 -0.98 -
34 8.4e+03 5.9 0.006 -1.2 -
35 8.4e+03 5.9 0.003 -1.4 -
36 8.4e+03 5.9 0.0015 -1.5 -
37 8.4e+03 5.9 0.00075 -1.4 -
38 8.4e+03 5.9 0.00037 -0.7 -
39 8.4e+03 5.9 0.00019 -0.13 -
40 8.4e+03 2 0.00019 0.64 +
41 8.4e+03 0.049 0.0019 0.99 ++
42 8.4e+03 0.31 0.019 1 ++
43 8.4e+03 0.041 0.19 1 ++
44 8.3e+03 0.6 0.19 0.9 +
45 8.2e+03 1.1 0.19 0.83 +
46 8.2e+03 0.47 0.19 0.89 +
47 8.1e+03 0.89 1.9 0.93 ++
48 8.1e+03 0.89 0.93 -2.4e+02 -
49 8.1e+03 0.89 0.47 -34 -
50 8.1e+03 0.031 4.7 1.1 ++
51 8.1e+03 2.2 47 1.1 ++
52 8e+03 5.1 4.7e+02 1.3 ++
53 8e+03 5.1 0.36 -3.3 -
54 8e+03 21 0.36 0.21 +
55 8e+03 5.1 3.6 0.94 ++
56 8e+03 0.67 36 0.97 ++
57 8e+03 0.0022 3.6e+02 1 ++
58 8e+03 0.00015 3.6e+03 1 ++
59 8e+03 0.00041 3.6e+04 1 ++
60 8e+03 1.9e-07 3.6e+04 1 ++
Optimization algorithm has converged.
Relative gradient: 1.868834031654573e-07
Cause of termination: Relative gradient = 1.9e-07 <= 6.1e-06
Number of function evaluations: 120
Number of gradient evaluations: 59
Number of hessian evaluations: 29
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 61
Proportion of Hessian calculation: 29/29 = 100.0%
Optimization time: 0:00:07.096324
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000013.iter
Cannot read file __b07everything_000013.iter. Statement is ignored.
Starting values for the algorithm: {}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.96 1 -0.72 -0.64 -0.31 -0.48 8.5e+03 0.043 10 1.1 ++
1 -1.1 1.4 -1.1 -0.69 -0.0034 -1.1 8.3e+03 0.0087 1e+02 1.1 ++
2 -1.1 1.5 -1.2 -0.7 0.014 -1.3 8.3e+03 0.0003 1e+03 1 ++
3 -1.1 1.5 -1.2 -0.7 0.014 -1.3 8.3e+03 5.2e-07 1e+03 1 ++
Optimization algorithm has converged.
Relative gradient: 5.196762190028907e-07
Cause of termination: Relative gradient = 5.2e-07 <= 6.1e-06
Number of function evaluations: 13
Number of gradient evaluations: 9
Number of hessian evaluations: 4
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 4
Proportion of Hessian calculation: 4/4 = 100.0%
Optimization time: 0:00:00.384050
Calculate second derivatives and BHHH
Pareto: 14
Considered: 432
Removed: 50
print(f'A total of {len(non_dominated_models)} models have been generated.')
A total of 14 models have been generated.
compiled_results, specs = compile_estimation_results(
non_dominated_models, use_short_names=True
)
display(compiled_results)
Model_000000 ... Model_000013
Number of estimated parameters 20 ... 6
Sample size 10719 ... 10719
Final log likelihood -8009.406 ... -8313.613
Akaike Information Criterion 16058.81 ... 16639.23
Bayesian Information Criterion 16204.41 ... 16682.9
asc_train_ref (t-test) -0.457 (-4.26) ... -1.12 (-18.2)
asc_train_diff_GA (t-test) 0.914 (10.3) ... 1.52 (22.1)
asc_train_diff_one_lugg (t-test) 0.322 (4.93) ...
asc_train_diff_several_lugg (t-test) 0.165 (1.06) ...
b_time_train_ref (t-test) -2.12 (-21.3) ...
b_time_train_diff_commuters (t-test) -0.143 (-0.887) ...
square_tt_coef (t-test) -0.102 (-24.7) ...
cube_tt_coef (t-test) 0.000184 (8.21) ...
b_cost_train (t-test) -0.702 (-7.6) ...
mu_existing (t-test) 1.74 (17.4) ...
asc_car_ref (t-test) -0.348 (-4.47) ... 0.0143 (0.361)
asc_car_diff_GA (t-test) -0.303 (-2.52) ... -1.26 (-8.18)
asc_car_diff_one_lugg (t-test) -0.0864 (-1.82) ...
asc_car_diff_several_lugg (t-test) -0.387 (-2.17) ...
b_time_car_ref (t-test) -1.63 (-17.3) ...
b_time_car_diff_commuters (t-test) -0.168 (-0.909) ...
b_cost_car (t-test) -0.539 (-7.32) ...
b_time_swissmetro_ref (t-test) -2.21 (-24.1) ...
b_time_swissmetro_diff_commuters (t-test) 0.647 (2.68) ...
b_cost_swissmetro (t-test) -0.628 (-12.9) ...
b_time_train_diff_1st_class (t-test) ...
lambda_travel_time (t-test) ...
b_cost (t-test) ... -0.704 (-13.3)
b_time_car_diff_1st_class (t-test) ...
b_time_swissmetro_diff_1st_class (t-test) ...
b_time_train (t-test) ...
b_time_car (t-test) ...
b_time_swissmetro (t-test) ...
b_time (t-test) ... -1.19 (-18.3)
asc_train (t-test) ...
asc_car (t-test) ...
b_time_ref (t-test) ...
b_time_diff_1st_class (t-test) ...
[38 rows x 14 columns]
Glossary
for short_name, spec in specs.items():
print(f'{short_name}\t{spec}')
Model_000000 asc:GA-LUGGAGE;b_cost_gen_altspec:altspec;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Model_000001 asc:GA;b_cost_gen_altspec:generic;b_time:FIRST;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:boxcox
Model_000002 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Model_000003 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:boxcox
Model_000004 asc:GA;b_cost_gen_altspec:generic;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Model_000005 asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:linear
Model_000006 asc:GA;b_cost_gen_altspec:altspec;b_time:FIRST;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:power
Model_000007 asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear
Model_000008 asc:GA;b_cost_gen_altspec:generic;b_time:FIRST;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:boxcox
Model_000009 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:boxcox
Model_000010 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:boxcox
Model_000011 asc:GA;b_cost_gen_altspec:altspec;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Model_000012 asc:GA-LUGGAGE;b_cost_gen_altspec:generic;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Model_000013 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear
Total running time of the script: (6 minutes 59.285 seconds)