.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/swissmetro/plot_b22a_multiple_models.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_swissmetro_plot_b22a_multiple_models.py: .. _plot_b22multiple_models: Assisted specification ====================== Example of the estimation of several versions of the model using assisted specification algorithm. The catalog of specifications is defined in :ref:`plot_b22multiple_models_spec` . Compared to :ref:`plot_b21multiple_models`, the number fo specifications exceeds the maximum limit, so a heuristic is applied. See `Bierlaire and Ortelli, 2023 `_ for a detailed description of the use of the assisted specification algorithm. Michel Bierlaire, EPFL Sat Jun 28 2025, 12:25:12 .. GENERATED FROM PYTHON SOURCE LINES 21-33 .. code-block:: Python import biogeme.biogeme_logging as blog from biogeme.assisted import AssistedSpecification from biogeme.catalog import count_number_of_specifications from biogeme.multiobjectives import aic_bic_dimension from biogeme.results_processing import compile_estimation_results from plot_b22b_multiple_models_spec import PARETO_FILE_NAME, the_biogeme logger = blog.get_screen_logger(blog.INFO) logger.info('Example b22multiple_models') .. rst-class:: sphx-glr-script-out .. code-block:: none Example b22multiple_models .. GENERATED FROM PYTHON SOURCE LINES 34-41 .. code-block:: Python nbr = count_number_of_specifications(the_biogeme.log_like) if nbr is None: print('There are too many possible specifications to be enumerated') else: print(f'There are {nbr} possible specifications') .. rst-class:: sphx-glr-script-out .. code-block:: none There are 504 possible specifications .. GENERATED FROM PYTHON SOURCE LINES 42-51 Creation of the object capturing the assisted specification algorithm. Its constructor takes three arguments: - the biogeme object containing the specifications and the database, - an object defining the objectives to minimize. Here, we use three objectives: AIC, BIC and number of parameters. - the name of the file where the estimated are saved, and organized into a Pareto set. .. GENERATED FROM PYTHON SOURCE LINES 51-57 .. code-block:: Python assisted_specification = AssistedSpecification( biogeme_object=the_biogeme, multi_objectives=aic_bic_dimension, pareto_file_name=PARETO_FILE_NAME, ) .. rst-class:: sphx-glr-script-out .. code-block:: none Unable to read file b22_multiple_models.pareto. Pareto set empty. .. GENERATED FROM PYTHON SOURCE LINES 58-59 The algorithm is run. .. GENERATED FROM PYTHON SOURCE LINES 59-61 .. code-block:: Python non_dominated_models = assisted_specification.run() .. rst-class:: sphx-glr-script-out .. code-block:: none Biogeme parameters read from biogeme.toml. Model with 4 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_time b_cost asc_car Function Relgrad Radius Rho 0 -0.92 -0.67 -0.88 -0.49 5.4e+03 0.041 10 1.1 ++ 1 -0.73 -1.2 -1 -0.18 5.3e+03 0.0072 1e+02 1.1 ++ 2 -0.7 -1.3 -1.1 -0.16 5.3e+03 0.00018 1e+03 1 ++ 3 -0.7 -1.3 -1.1 -0.16 5.3e+03 1.1e-07 1e+03 1 ++ default_specification=asc:no_seg;train_cost_catalog:linear;train_headway_catalog:without_headway;train_tt_catalog:linear The number of possible specifications [504] exceeds the maximum number [100]. A heuristic algorithm is applied. *** VNS *** asc:no_seg;train_cost_catalog:linear;train_headway_catalog:without_headway;train_tt_catalog:linear [10670.504013832326, np.float64(10697.78385743747), 4] Initial pareto: 1 Attempt 0/100 Biogeme parameters read from biogeme.toml. Model with 4 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_time b_cost asc_car Function Relgrad Radius Rho 0 -1 -1 -0.38 -0.11 5.6e+03 0.041 10 1.1 ++ 1 -0.65 -2.8 -0.89 -0.037 5.3e+03 0.016 1e+02 1.1 ++ 2 -0.49 -3.3 -1.1 -0.0039 5.3e+03 0.0015 1e+03 1.1 ++ 3 -0.48 -3.4 -1.1 -0.0026 5.3e+03 9.8e-06 1e+04 1 ++ 4 -0.48 -3.4 -1.1 -0.0026 5.3e+03 4.4e-10 1e+04 1 ++ Considering neighbor 0/20 for current solution *** New pareto solution: asc:no_seg;train_cost_catalog:linear;train_headway_catalog:without_headway;train_tt_catalog:sqrt [10592.228471637549, np.float64(10619.508315242692), 4] Attempt 1/100 Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_time lambda_tt b_cost b_headway asc_car Function Relgrad Radius Rho 0 -0.68 -0.99 1.8 -1 -0.0017 -0.46 5.7e+03 1.6 1 0.71 + 1 -0.7 -1.7 0.83 -1.3 0.00048 -0.15 5.4e+03 0.19 10 0.92 ++ 2 -0.15 -1.7 0.59 -1.1 -0.0062 -0.13 5.3e+03 0.076 1e+02 0.98 ++ 3 -0.23 -1.7 0.51 -1.1 -0.0054 -0.11 5.3e+03 0.0013 1e+03 1 ++ 4 -0.23 -1.7 0.51 -1.1 -0.0054 -0.11 5.3e+03 6.9e-07 1e+03 1 ++ Considering neighbor 0/20 for current solution *** New pareto solution: asc:no_seg;train_cost_catalog:linear;train_headway_catalog:with_headway;train_tt_catalog:boxcox [10564.70646462865, np.float64(10605.626230036367), 6] Attempt 2/100 Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. Function Relgrad Radius Rho 0 5.5e+03 0.037 10 1.1 ++ 1 5.4e+03 0.0086 1e+02 1.1 ++ 2 5.4e+03 0.00081 1e+03 1.1 ++ 3 5.4e+03 7.7e-06 1e+04 1 ++ 4 5.4e+03 7.3e-10 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.76 0.19 -1 -0.37 -0.27 -0.12 5.4e+03 0.044 10 1 ++ 1 -0.97 2.4 -1.6 -0.96 -0.072 -0.11 5e+03 0.027 1e+02 0.94 ++ 2 -1 2.1 -1.7 -1.1 -0.067 -0.29 5e+03 0.00066 1e+03 1 ++ 3 -1 2.1 -1.7 -1.1 -0.067 -0.29 5e+03 2.1e-06 1e+03 1 ++ Considering neighbor 1/20 for current solution *** New pareto solution: asc:GA;train_cost_catalog:linear;train_headway_catalog:without_headway;train_tt_catalog:log [10054.467818928895, np.float64(10095.387584336611), 6] Attempt 3/100 Biogeme parameters read from biogeme.toml. Model with 5 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_time b_cost b_headway asc_car Function Relgrad Radius Rho 0 -0.53 -1 -0.36 -0.0041 -0.52 5.5e+03 2.4 10 1 ++ 1 -0.32 -1.6 -0.94 -0.0046 -0.081 5.3e+03 0.041 1e+02 1 ++ 2 -0.25 -1.7 -1 -0.0054 -0.11 5.3e+03 0.012 1e+03 1 ++ 3 -0.25 -1.7 -1 -0.0054 -0.11 5.3e+03 0.00025 1e+04 1 ++ 4 -0.25 -1.7 -1 -0.0054 -0.11 5.3e+03 1.2e-05 1e+05 1 ++ 5 -0.25 -1.7 -1 -0.0054 -0.11 5.3e+03 2.7e-07 1e+05 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.74 0.21 -1 -0.26 -0.29 -0.13 5.5e+03 0.044 10 1 ++ 1 -1.1 2.4 -1.5 -1.3 -0.13 -1.2 5e+03 0.028 1e+02 0.96 ++ 2 -1.2 2.2 -1.6 -1.5 -0.16 -1.8 5e+03 0.00079 1e+03 1 ++ 3 -1.2 2.2 -1.6 -1.5 -0.16 -1.8 5e+03 4.9e-06 1e+03 1 ++ Considering neighbor 1/20 for current solution *** New pareto solution: asc:GA;train_cost_catalog:log;train_headway_catalog:without_headway;train_tt_catalog:log [9913.311849260816, np.float64(9954.231614668532), 6] Attempt 4/100 Biogeme parameters read from biogeme.toml. Model with 4 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_time b_cost asc_car Function Relgrad Radius Rho 0 -0.74 -1 -0.39 -0.3 5.5e+03 0.044 10 1 ++ 1 -0.54 -1.6 -0.93 -0.0041 5.3e+03 0.0052 1e+02 1.1 ++ 2 -0.51 -1.7 -1 0.0019 5.3e+03 0.00015 1e+03 1 ++ 3 -0.51 -1.7 -1 0.0019 5.3e+03 1.4e-07 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.53 -0.72 0.42 0.081 -0.62 -0.9 -0.0027 -0.74 -0.0034 0.23 -0.048 5.3e+03 2.6 10 1.1 ++ 1 -0.32 -1 0.76 0.39 -1.1 -1.1 -0.0051 -0.65 0.29 0.12 -0.09 5.1e+03 0.46 1e+02 1.1 ++ 2 -0.39 -1.1 0.94 0.55 -1.2 -1.1 -0.0059 -0.68 0.33 0.12 -0.085 5.1e+03 0.037 1e+03 1 ++ 3 -0.41 -1.1 0.96 0.58 -1.2 -1.1 -0.006 -0.68 0.33 0.12 -0.067 5.1e+03 0.00034 1e+04 1 ++ 4 -0.41 -1.1 0.96 0.58 -1.2 -1.1 -0.006 -0.68 0.33 0.12 -0.067 5.1e+03 1.3e-06 1e+04 1 ++ Considering neighbor 1/20 for current solution Considering neighbor 2/20 for current solution Attempt 5/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ asc_train_diff_ b_time b_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.42 -0.75 0.79 -0.7 -1 -0.00052 -0.39 -0.095 -0.36 5.2e+03 2.8 10 1.1 ++ 1 -0.49 -0.92 1.9 -0.96 -1.4 -0.0048 -0.8 0.37 -1.4 4.9e+03 0.74 1e+02 1.1 ++ 2 -0.43 -1.1 2 -1 -1.4 -0.0066 -0.91 0.46 -1.9 4.9e+03 0.069 1e+03 1.1 ++ 3 -0.42 -1.1 2 -1 -1.5 -0.0068 -0.91 0.47 -1.9 4.9e+03 0.00065 1e+04 1 ++ 4 -0.42 -1.1 2 -1 -1.5 -0.0068 -0.91 0.47 -1.9 4.9e+03 1.1e-05 1e+05 1 ++ 5 -0.42 -1.1 2 -1 -1.5 -0.0068 -0.91 0.47 -1.9 4.9e+03 8.8e-09 1e+05 1 ++ Considering neighbor 0/20 for current solution *** New pareto solution: asc:MALE-GA;train_cost_catalog:log;train_headway_catalog:with_headway;train_tt_catalog:linear [9765.322555569284, np.float64(9826.70220368086), 9] Attempt 6/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.7 -0.7 0.42 0.1 -0.59 -0.94 -0.68 0.0075 0.12 -0.41 5.3e+03 0.038 10 1.1 ++ 1 -0.72 -1 0.76 0.37 -0.97 -1.1 -0.6 0.31 -0.023 -0.5 5.2e+03 0.0081 1e+02 1.1 ++ 2 -0.84 -1.1 0.94 0.53 -1 -1.1 -0.6 0.33 -0.023 -0.51 5.2e+03 0.00052 1e+03 1 ++ 3 -0.84 -1.1 0.94 0.53 -1 -1.1 -0.6 0.33 -0.023 -0.51 5.2e+03 4.4e-06 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. asc_train_ref asc_train_diff_ asc_train_diff_ b_time lambda_tt b_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.52 -0.79 0.53 -0.88 1.7 -1 0.003 -0.29 -0.051 -0.22 5.3e+03 2.3 1 0.88 + 1 -0.29 -1 1.5 -1.1 1 -1 -0.0043 -0.51 0.087 -0.35 4.9e+03 0.6 10 1.1 ++ 2 0.43 -1.1 1.9 -2.2 -0.078 -1.1 -0.0066 -0.37 0.46 -0.44 4.9e+03 0.14 10 0.21 + 3 0.15 -1.2 2 -1.8 0.17 -1.1 -0.0066 -0.51 0.4 -0.44 4.9e+03 0.0078 1e+02 1.1 ++ 4 0.11 -1.2 2 -1.7 0.33 -1.1 -0.0067 -0.54 0.41 -0.43 4.9e+03 0.0043 1e+03 1 ++ 5 0.098 -1.2 2 -1.7 0.34 -1.1 -0.0067 -0.55 0.41 -0.43 4.9e+03 4.7e-05 1e+04 1 ++ 6 0.098 -1.2 2 -1.7 0.34 -1.1 -0.0067 -0.55 0.41 -0.43 4.9e+03 2.1e-07 1e+04 1 ++ Considering neighbor 1/20 for current solution *** New pareto solution: asc:MALE-GA;train_cost_catalog:linear;train_headway_catalog:with_headway;train_tt_catalog:boxcox [9742.605177445377, np.float64(9810.804786458239), 10] Attempt 7/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost lambda_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.66 -0.088 -0.015 -1 -0.3 1 -0.35 -0.27 -0.022 5.6e+03 0.057 10 1 ++ 1 -0.66 -0.088 -0.015 -1 -0.3 1 -0.35 -0.27 -0.022 5.6e+03 0.057 4.5 -2.9e+05 - 2 -0.66 -0.088 -0.015 -1 -0.3 1 -0.35 -0.27 -0.022 5.6e+03 0.057 2.2 -1.3e+02 - 3 -0.66 -0.088 -0.015 -1 -0.3 1 -0.35 -0.27 -0.022 5.6e+03 0.057 1.1 -4.7 - 4 -1.1 0.83 0.97 -1.6 -0.86 2.1 0.0079 -0.16 -0.75 5.6e+03 0.089 1.1 0.13 + 5 -1.1 0.83 0.97 -1.6 -0.86 2.1 0.0079 -0.16 -0.75 5.6e+03 0.089 0.56 -1.2 - 6 -1.1 1.1 0.92 -1.6 -0.3 2.1 0.12 -0.074 -0.72 5.4e+03 0.012 0.56 0.89 + 7 -1.3 1.1 0.91 -1.7 -0.56 1.5 0.0027 -0.18 -0.7 5.4e+03 0.031 5.6 0.96 ++ 8 -1.3 1.1 0.91 -1.7 -0.56 1.5 0.0027 -0.18 -0.7 5.4e+03 0.031 1.1 -1.5 - 9 -1.3 1.1 0.92 -1.6 -0.9 0.41 0.02 0.017 -0.68 5.3e+03 0.0093 11 0.95 ++ 10 -1.4 1.2 1 -1.5 -1.1 0.41 -0.084 -0.068 -0.65 5.3e+03 0.00049 1.1e+02 1 ++ 11 -1.4 1.2 1 -1.5 -1.1 0.41 -0.084 -0.068 -0.65 5.3e+03 5.2e-06 1.1e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. asc_train_ref asc_train_diff_ asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -1 0.25 0.0045 -0.71 -0.89 -0.39 -0.075 -0.066 5.4e+03 0.044 10 1.1 ++ 1 -1.3 0.89 0.74 -1.2 -1.1 -0.26 0.1 -0.22 5.2e+03 0.0092 1e+02 1.1 ++ 2 -1.5 1.1 0.95 -1.2 -1.1 -0.24 0.1 -0.25 5.2e+03 0.00096 1e+03 1.1 ++ 3 -1.5 1.1 0.98 -1.2 -1.1 -0.24 0.1 -0.25 5.2e+03 1.1e-05 1e+04 1 ++ 4 -1.5 1.1 0.98 -1.2 -1.1 -0.24 0.1 -0.25 5.2e+03 1.7e-09 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -1 0.15 -1 -0.35 -0.045 -1 5.5e+03 0.043 10 1.1 ++ 1 -1.2 2.3 -2.4 -1.2 -0.18 -1.4 5e+03 0.026 1e+02 1 ++ 2 -1.2 2.1 -2.9 -1.4 -0.19 -1.9 4.9e+03 0.0017 1e+03 1 ++ 3 -1.2 2.1 -2.9 -1.5 -0.19 -1.9 4.9e+03 1.5e-05 1e+04 1 ++ 4 -1.2 2.1 -2.9 -1.5 -0.19 -1.9 4.9e+03 1.4e-09 1e+04 1 ++ Considering neighbor 2/20 for current solution *** New pareto solution: asc:GA;train_cost_catalog:log;train_headway_catalog:without_headway;train_tt_catalog:sqrt [9905.779868217465, np.float64(9946.699633625181), 6] Attempt 8/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. asc_train_ref asc_train_diff_ asc_train_diff_ b_time b_cost beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_on asc_car_diff_se beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.52 0.052 -0.0022 -1 0 0 0 -0.0028 0 0 -0.25 -0.14 -0.034 0 0 5.6e+03 2.5 10 1 ++ 1 -0.7 0.81 0.63 -1.5 0 0 0 -0.0047 0 0 0.15 -0.089 -0.71 0 0 5.5e+03 0.44 1e+02 1.1 ++ 2 -0.94 1.1 0.9 -1.6 0 0 0 -0.0053 0 0 0.13 -0.081 -0.76 0 0 5.5e+03 0.05 1e+03 1.1 ++ 3 -0.98 1.1 0.94 -1.6 0 0 0 -0.0053 0 0 0.13 -0.082 -0.76 0 0 5.5e+03 0.00074 1e+04 1 ++ 4 -0.98 1.1 0.94 -1.6 0 0 0 -0.0053 0 0 0.13 -0.082 -0.76 0 0 5.5e+03 2e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost lambda_cost asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.86 0.79 -0.82 -1 1 -0.48 -0.37 5.3e+03 0.04 10 1.1 ++ 1 -1.4 2 -1 -1.9 -0.36 -0.45 -1.5 5.1e+03 0.054 10 0.67 + 2 -1.5 2.1 -0.98 -1.3 -0.3 -0.34 -1.8 5e+03 0.0023 1e+02 1 ++ 3 -1.5 2.1 -1 -1.6 0.14 -0.38 -1.8 5e+03 0.0071 1e+02 0.82 + 4 -1.5 2.1 -1.1 -1.5 0.12 -0.35 -1.8 5e+03 0.00014 1e+03 0.99 ++ 5 -1.5 2.1 -1.1 -1.5 0.12 -0.35 -1.8 5e+03 1.3e-06 1e+03 1 ++ Considering neighbor 1/20 for current solution Considering neighbor 2/20 for current solution Attempt 9/100 Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost lambda_cost asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.36 -0.57 -1 -0.74 1 -0.35 -0.15 5.4e+03 0.037 10 1 ++ 1 0.28 -1.3 -1.5 -1.3 -0.089 -0.39 0.24 5.3e+03 0.016 10 0.8 + 2 0.27 -1.3 -1.6 -1.2 0.22 -0.41 0.29 5.2e+03 0.0039 1e+02 1.2 ++ 3 0.3 -1.3 -1.6 -1.1 0.4 -0.39 0.28 5.2e+03 0.00075 1e+03 1.1 ++ 4 0.3 -1.3 -1.6 -1.1 0.43 -0.38 0.28 5.2e+03 1.7e-05 1e+04 1 ++ 5 0.3 -1.3 -1.6 -1.1 0.43 -0.38 0.28 5.2e+03 2.4e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.42 -0.58 0.49 -1 -0.61 -0.36 -0.18 -0.22 5.3e+03 0.052 10 1 ++ 1 -0.4 -0.96 2.1 -1.5 -1.4 -0.47 0.37 -1.4 4.8e+03 0.021 1e+02 1 ++ 2 -0.37 -1.2 2.1 -1.6 -1.5 -0.55 0.45 -1.9 4.8e+03 0.0012 1e+03 1 ++ 3 -0.37 -1.2 2.1 -1.6 -1.5 -0.55 0.46 -2 4.8e+03 9.3e-06 1e+04 1 ++ 4 -0.37 -1.2 2.1 -1.6 -1.5 -0.55 0.46 -2 4.8e+03 3e-09 1e+04 1 ++ Considering neighbor 1/20 for current solution *** New pareto solution: asc:MALE-GA;train_cost_catalog:log;train_headway_catalog:without_headway;train_tt_catalog:log [9676.555372350647, np.float64(9731.115059560936), 8] Attempt 10/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost lambda_cost b_headway asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.37 -0.65 -1 -0.7 1 0.0011 -0.31 -0.075 5.4e+03 2.5 10 1 ++ 1 0.52 -1.3 -1.5 -1.3 -0.13 -0.0045 -0.44 0.19 5.2e+03 0.61 10 0.78 + 2 0.55 -1.3 -1.6 -1.2 0.2 -0.0057 -0.53 0.29 5.2e+03 0.044 1e+02 1.2 ++ 3 0.57 -1.3 -1.6 -1.1 0.39 -0.0058 -0.5 0.28 5.2e+03 0.0026 1e+03 1.1 ++ 4 0.58 -1.3 -1.6 -1.1 0.43 -0.0058 -0.5 0.28 5.2e+03 0.00011 1e+04 1 ++ 5 0.58 -1.3 -1.6 -1.1 0.43 -0.0058 -0.5 0.28 5.2e+03 1.7e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost lambda_cost asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.57 -0.76 -1 -0.96 1 -0.54 -0.25 5.4e+03 0.034 10 1 ++ 1 0.16 -1.2 -2.8 -1.3 0.38 -0.46 0.27 5.2e+03 0.013 1e+02 1 ++ 2 0.24 -1.3 -3 -1.1 0.53 -0.44 0.33 5.2e+03 0.00083 1e+03 1.1 ++ 3 0.25 -1.3 -3.1 -1.1 0.58 -0.43 0.33 5.2e+03 5.1e-05 1e+04 1 ++ 4 0.25 -1.3 -3.1 -1.1 0.58 -0.43 0.33 5.2e+03 2.8e-08 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.22 -0.6 -1 0 0 0 -0.0001 0 0 -0.25 0.0035 0 0 5.5e+03 2.7 10 1 ++ 1 0.67 -1.2 -1.5 0 0 0 -0.0046 0 0 -0.15 0.27 0 0 5.4e+03 0.46 1e+02 1 ++ 2 0.72 -1.3 -1.6 0 0 0 -0.0056 0 0 -0.17 0.27 0 0 5.4e+03 0.021 1e+03 1 ++ 3 0.72 -1.3 -1.6 0 0 0 -0.0057 0 0 -0.17 0.27 0 0 5.4e+03 4.4e-05 1e+04 1 ++ 4 0.72 -1.3 -1.6 0 0 0 -0.0057 0 0 -0.17 0.27 0 0 5.4e+03 2e-10 1e+04 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.37 -0.59 -1 -0.89 -0.33 -0.13 5.3e+03 0.036 10 1 ++ 1 0.4 -1.3 -1.6 -1 -0.22 0.22 5.2e+03 0.0091 1e+02 1 ++ 2 0.4 -1.3 -1.7 -1 -0.24 0.25 5.2e+03 0.00022 1e+03 1 ++ 3 0.4 -1.3 -1.7 -1 -0.24 0.25 5.2e+03 2.4e-07 1e+03 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ asc_train_diff_ b_time b_cost lambda_cost asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.65 -0.8 0.7 -1 -0.96 1 -0.56 -0.28 -0.31 5.3e+03 0.041 10 1 ++ 1 -0.65 -0.8 0.7 -1 -0.96 1 -0.56 -0.28 -0.31 5.3e+03 0.041 0.93 -0.12 - 2 -0.73 -1.2 1.6 -1.7 -0.88 0.53 -0.53 0.072 -0.64 5e+03 0.02 9.3 1.1 ++ 3 -0.73 -1.2 1.6 -1.7 -0.88 0.53 -0.53 0.072 -0.64 5e+03 0.02 0.83 -3 - 4 -0.64 -1.2 2.2 -2.5 -1.5 0.1 -0.63 0.31 -1.1 4.9e+03 0.0057 8.3 1 ++ 5 -0.46 -1.1 2 -3 -1.5 0.089 -0.6 0.47 -1.8 4.8e+03 0.0013 83 1.1 ++ 6 -0.46 -1.1 2 -3 -1.5 0.085 -0.61 0.48 -2 4.8e+03 6.5e-05 8.3e+02 1 ++ 7 -0.46 -1.1 2 -3 -1.5 0.085 -0.61 0.48 -2 4.8e+03 1.7e-07 8.3e+02 1 ++ Considering neighbor 4/20 for current solution Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.61 -0.75 -0.91 -1 -0.5 -0.25 5.4e+03 0.034 10 1 ++ 1 0.25 -1.2 -3 -1 -0.28 0.24 5.1e+03 0.015 1e+02 1.1 ++ 2 0.34 -1.3 -3.3 -1.1 -0.3 0.3 5.1e+03 0.00068 1e+03 1 ++ 3 0.34 -1.3 -3.3 -1.1 -0.3 0.3 5.1e+03 1.3e-06 1e+03 1 ++ Considering neighbor 5/20 for current solution Considering neighbor 6/20 for current solution Attempt 11/100 Considering neighbor 0/20 for current solution Attempt 12/100 Considering neighbor 0/20 for current solution Attempt 13/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ asc_train_diff_ asc_train_diff_ b_time b_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.58 -0.69 0.43 0.12 -0.58 -0.94 -0.0027 -0.75 0.011 0.12 -0.35 5.3e+03 2.7 10 1.1 ++ 1 -0.47 -1 0.77 0.37 -0.96 -1.1 -0.0051 -0.7 0.31 -0.022 -0.48 5.2e+03 0.45 1e+02 1.1 ++ 2 -0.56 -1.1 0.95 0.52 -1 -1.1 -0.0059 -0.72 0.33 -0.021 -0.51 5.2e+03 0.036 1e+03 1.1 ++ 3 -0.57 -1.1 0.97 0.55 -1 -1.1 -0.0059 -0.72 0.33 -0.022 -0.5 5.2e+03 0.00032 1e+04 1 ++ 4 -0.57 -1.1 0.97 0.55 -1 -1.1 -0.0059 -0.72 0.33 -0.022 -0.5 5.2e+03 1.1e-06 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. asc_train_ref asc_train_diff_ asc_train_diff_ b_time lambda_tt b_cost asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.45 -0.67 0.68 -0.95 2 -0.91 -0.5 -0.27 -0.33 5.8e+03 0.14 1 0.58 + 1 -0.78 -1.3 1.7 -0.38 1.8 -1.1 -0.53 0.15 -0.9 5.1e+03 0.028 10 0.95 ++ 2 -0.78 -1.3 1.7 -0.38 1.8 -1.1 -0.53 0.15 -0.9 5.1e+03 0.028 5 -2.5e+03 - 3 -0.78 -1.3 1.7 -0.38 1.8 -1.1 -0.53 0.15 -0.9 5.1e+03 0.028 2.5 -13 - 4 -0.78 -1.3 1.7 -0.38 1.8 -1.1 -0.53 0.15 -0.9 5.1e+03 0.028 1.2 0.071 - 5 -1.1 -1.3 2 -0.92 0.56 -1.5 -0.72 0.23 -1.2 4.9e+03 0.031 12 0.95 ++ 6 -0.34 -1.1 2.1 -1.7 -0.041 -1.5 -0.51 0.46 -1.8 4.8e+03 0.0035 12 0.82 + 7 -0.34 -1.1 2.1 -1.7 0.21 -1.5 -0.54 0.49 -2 4.8e+03 0.0038 1.2e+02 0.99 ++ 8 -0.39 -1.1 2.1 -1.6 0.22 -1.5 -0.56 0.48 -2 4.8e+03 4.7e-05 1.2e+03 0.99 ++ 9 -0.39 -1.1 2.1 -1.6 0.22 -1.5 -0.56 0.48 -2 4.8e+03 7.9e-09 1.2e+03 1 ++ Considering neighbor 1/20 for current solution *** New pareto solution: asc:MALE-GA;train_cost_catalog:log;train_headway_catalog:without_headway;train_tt_catalog:boxcox [9664.011630249151, np.float64(9725.391278360727), 9] Attempt 14/100 Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost lambda_cost asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -1 0.11 -1 -0.27 1.1 -0.047 -1 5.6e+03 0.042 10 1.1 ++ 1 -1 0.11 -1 -0.27 1.1 -0.047 -1 5.6e+03 0.042 5 -1.4e+07 - 2 -1 0.11 -1 -0.27 1.1 -0.047 -1 5.6e+03 0.042 2.5 -2.1e+02 - 3 -1 0.11 -1 -0.27 1.1 -0.047 -1 5.6e+03 0.042 1.2 -0.26 - 4 -1.4 1.4 -1.9 -1.1 0.99 -0.38 -1.1 5.1e+03 0.023 12 1.1 ++ 5 -1.4 1.4 -1.9 -1.1 0.99 -0.38 -1.1 5.1e+03 0.023 1.2 -12 - 6 -1.3 2.5 -3 -2 -0.19 -0.31 -1.4 5e+03 0.041 1.2 0.5 + 7 -1.3 2.1 -2.9 -1.4 -0.13 -0.18 -1.8 5e+03 0.0015 12 0.98 ++ 8 -1.2 2.1 -3 -1.5 0.1 -0.19 -1.9 4.9e+03 0.002 1.2e+02 0.91 ++ 9 -1.2 2.1 -3 -1.5 0.091 -0.19 -1.9 4.9e+03 1.9e-05 1.2e+03 1 ++ 10 -1.2 2.1 -3 -1.5 0.091 -0.19 -1.9 4.9e+03 2.3e-08 1.2e+03 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 15/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 lambda_tt b_cost asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.46 -0.64 0.57 -0.92 1.9 -1 -0.45 -0.25 -0.24 5.5e+03 0.087 1 0.73 + 1 -0.56 -1.1 1.6 -1 1.2 -0.95 -0.47 0.12 -0.36 5e+03 0.019 10 1.2 ++ 2 -0.56 -1.1 1.6 -1 1.2 -0.95 -0.47 0.12 -0.36 5e+03 0.019 1.6 -11 - 3 -0.56 -1.1 1.6 -1 1.2 -0.95 -0.47 0.12 -0.36 5e+03 0.019 0.8 -0.46 - 4 -0.55 -1.2 1.9 -1.5 0.42 -1.1 -0.48 0.3 -0.4 4.9e+03 0.017 8 0.99 ++ 5 -0.21 -1.1 1.9 -1.7 0.33 -1.1 -0.42 0.41 -0.45 4.9e+03 0.00079 80 0.98 ++ 6 -0.21 -1.1 1.9 -1.7 0.33 -1.1 -0.42 0.41 -0.45 4.9e+03 3.4e-06 80 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost lambda_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.37 -0.71 0.82 -0.68 -1 1 -0.0024 -0.47 -0.17 -0.36 5.2e+03 2.6 10 1.1 ++ 1 -0.48 -0.93 1.9 -0.98 -1.9 -0.44 -0.0054 -0.89 0.34 -1.5 5e+03 0.88 10 0.6 + 2 -0.48 -1.1 2 -0.95 -1.1 -0.44 -0.0065 -0.88 0.49 -1.9 4.9e+03 0.088 1e+02 0.95 ++ 3 -0.42 -1.1 2 -1 -1.7 0.27 -0.0068 -0.96 0.47 -2 4.9e+03 0.05 1e+02 0.48 + 4 -0.38 -1.1 2 -1.1 -1.5 0.17 -0.0069 -0.89 0.45 -1.9 4.9e+03 0.011 1e+03 1 ++ 5 -0.4 -1.1 2 -1 -1.5 0.1 -0.0068 -0.9 0.46 -1.9 4.9e+03 0.00016 1e+04 0.99 ++ 6 -0.4 -1.1 2 -1 -1.5 0.1 -0.0068 -0.9 0.46 -1.9 4.9e+03 5.9e-07 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ b_time lambda_tt b_cost asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.43 -0.62 -0.89 1.8 -1 -0.45 -0.24 5.6e+03 0.083 1 0.72 + 1 0.39 -1.5 -1.6 0.85 -1 -0.65 0.58 5.2e+03 0.028 10 0.94 ++ 2 0.48 -1.3 -1.9 0.42 -1.1 -0.21 0.3 5.1e+03 0.0096 1e+02 0.95 ++ 3 0.36 -1.3 -1.7 0.45 -1.1 -0.29 0.3 5.1e+03 0.0004 1e+03 0.98 ++ 4 0.36 -1.3 -1.7 0.45 -1.1 -0.29 0.3 5.1e+03 6.7e-07 1e+03 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time lambda_tt b_cost asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.46 -0.67 0.2 -0.012 -0.9 1.8 -1 -0.33 -0.15 -0.23 -0.037 5.5e+03 0.064 1 0.78 + 1 -0.4 -1.3 1.1 0.055 -1.6 0.8 -1 -0.44 0.26 0.15 -0.11 5.1e+03 0.016 10 0.99 ++ 2 -0.31 -1.1 0.94 0.62 -1.8 0.42 -1.1 -0.31 0.33 0.069 -0.16 5.1e+03 0.0071 1e+02 0.95 ++ 3 -0.41 -1.1 0.95 0.55 -1.7 0.44 -1.1 -0.35 0.31 0.075 -0.15 5.1e+03 0.00024 1e+03 0.99 ++ 4 -0.41 -1.1 0.95 0.55 -1.7 0.44 -1.1 -0.35 0.31 0.075 -0.15 5.1e+03 2.3e-07 1e+03 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost b_headway beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_ma beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.63 -0.89 0 0 0 -0.88 -0.0029 0 0 -0.94 -0.049 0 0 5.5e+03 2.6 10 1 ++ 1 -0.5 -1.3 0 0 0 -0.94 -0.0053 0 0 -1.1 0.15 0 0 5.5e+03 0.33 1e+02 1.1 ++ 2 -0.47 -1.4 0 0 0 -0.95 -0.0059 0 0 -1.1 0.14 0 0 5.5e+03 0.012 1e+03 1 ++ 3 -0.47 -1.4 0 0 0 -0.95 -0.0059 0 0 -1.1 0.14 0 0 5.5e+03 1.7e-05 1e+04 1 ++ 4 -0.47 -1.4 0 0 0 -0.95 -0.0059 0 0 -1.1 0.14 0 0 5.5e+03 3e-11 1e+04 1 ++ Considering neighbor 4/20 for current solution Considering neighbor 5/20 for current solution Attempt 16/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time lambda_tt b_cost b_headway asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -0.67 0.026 -0.0067 0.56 -1 1.8 -0.99 -0.0027 -0.35 -0.18 -0.041 -0.23 5.5e+03 1.8 1 0.77 + 1 -1 0.47 0.027 1.6 -1.4 0.98 -0.98 -0.0067 -0.46 0.0012 -0.084 -0.33 5e+03 0.57 10 1.1 ++ 2 -0.82 0.66 0.43 1.8 -2.2 0.14 -1.1 -0.0062 0.021 0.007 -0.35 -0.34 5e+03 0.044 10 0.58 + 3 -1.2 0.71 0.47 1.9 -1.7 0.29 -1.1 -0.0062 -0.2 0.025 -0.32 -0.24 5e+03 0.0028 1e+02 1 ++ 4 -1.2 0.71 0.48 1.9 -1.7 0.38 -1.1 -0.0062 -0.21 0.029 -0.3 -0.26 4.9e+03 0.00098 1e+03 0.98 ++ 5 -1.2 0.71 0.48 1.9 -1.7 0.38 -1.1 -0.0062 -0.21 0.029 -0.3 -0.26 4.9e+03 6.2e-07 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 lambda_tt b_cost b_headway asc_car Function Relgrad Radius Rho 0 -0.71 -0.96 2 -0.77 -0.00097 -0.42 6e+03 1.9 1 0.55 + 1 -0.75 -0.47 1.9 -1.8 -0.0059 -0.26 5.5e+03 0.32 10 0.92 ++ 2 -0.75 -0.47 1.9 -1.8 -0.0059 -0.26 5.5e+03 0.32 3 -55 - 3 -0.75 -0.47 1.9 -1.8 -0.0059 -0.26 5.5e+03 0.32 1.5 -1.7 - 4 -0.76 -1.4 0.36 -2.2 -9.1e-05 -0.023 5.3e+03 0.25 1.5 0.79 + 5 -0.23 -1.7 0.54 -2.3 -0.0053 -0.045 5.2e+03 0.061 15 0.92 ++ 6 -0.25 -1.7 0.48 -2.4 -0.0053 -0.048 5.2e+03 0.00024 1.5e+02 1 ++ 7 -0.25 -1.7 0.48 -2.4 -0.0053 -0.048 5.2e+03 2.1e-06 1.5e+02 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time b_cost b_headway asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -0.53 -0.061 -0.0074 0.31 -1 -0.5 -0.0042 -0.4 -0.22 -0.027 -0.14 5.4e+03 2.4 10 1 ++ 1 -0.93 0.41 0.2 2.1 -1.6 -0.99 -0.0052 -0.19 0.017 -0.2 -0.21 5e+03 1.1 1e+02 0.99 ++ 2 -1.2 0.67 0.4 2 -1.7 -1.1 -0.006 -0.2 0.0097 -0.3 -0.22 5e+03 0.082 1e+03 1 ++ 3 -1.2 0.72 0.45 2 -1.7 -1.1 -0.0062 -0.2 0.0086 -0.3 -0.2 5e+03 0.0016 1e+04 1 ++ 4 -1.2 0.72 0.45 2 -1.7 -1.1 -0.0062 -0.2 0.0086 -0.3 -0.2 5e+03 8.9e-07 1e+04 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 17/100 Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost b_headway asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.95 0.38 -1 -0.61 -0.0045 -0.85 -0.21 5.4e+03 2.4 10 1 ++ 1 -0.76 2.1 -2.9 -1 -0.0053 -0.22 -0.29 5e+03 0.91 1e+02 0.99 ++ 2 -0.77 2 -3.2 -1.1 -0.0061 -0.21 -0.29 5e+03 0.045 1e+03 1 ++ 3 -0.77 2 -3.2 -1.1 -0.0062 -0.21 -0.3 5e+03 0.00024 1e+04 1 ++ 4 -0.77 2 -3.2 -1.1 -0.0062 -0.21 -0.3 5e+03 9.4e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.66 -0.081 -0.015 -1 -0.29 -0.35 -0.27 -0.023 5.6e+03 0.058 10 1 ++ 1 -1.1 0.8 0.64 -1.5 -1.1 -0.072 -0.072 -0.68 5.3e+03 0.013 1e+02 1 ++ 2 -1.4 1.1 0.94 -1.5 -1.1 -0.083 -0.081 -0.72 5.3e+03 0.0014 1e+03 1.1 ++ 3 -1.5 1.2 0.99 -1.5 -1.1 -0.082 -0.083 -0.73 5.3e+03 2.9e-05 1e+04 1 ++ 4 -1.5 1.2 0.99 -1.5 -1.1 -0.082 -0.083 -0.73 5.3e+03 1.1e-08 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ b_time b_cost b_headway asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.53 0.21 -1 -0.24 -0.0043 -0.52 -0.14 5.5e+03 2.5 10 1 ++ 1 -0.88 2.4 -1.4 -1.3 -0.0052 -0.24 -1.3 5e+03 0.97 1e+02 0.96 ++ 2 -0.92 2.2 -1.6 -1.5 -0.006 -0.28 -1.8 4.9e+03 0.029 1e+03 1 ++ 3 -0.92 2.2 -1.6 -1.5 -0.0061 -0.28 -1.8 4.9e+03 0.00023 1e+04 1 ++ 4 -0.92 2.2 -1.6 -1.5 -0.0061 -0.28 -1.8 4.9e+03 5.6e-06 1e+04 1 ++ Considering neighbor 2/20 for current solution *** New pareto solution: asc:GA;train_cost_catalog:log;train_headway_catalog:with_headway;train_tt_catalog:log [9879.020121111203, np.float64(9926.759847420206), 7] Attempt 18/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.33 -0.57 0.63 -1 0 0 0 0 0 -0.27 -0.067 -0.26 0 0 5.4e+03 0.048 10 1 ++ 1 -0.054 -0.99 1.7 -1.6 0 0 0 0 0 -0.078 0.37 -1.1 0 0 5.1e+03 0.016 1e+02 1 ++ 2 -0.058 -1.2 1.8 -1.6 0 0 0 0 0 -0.1 0.39 -1.4 0 0 5.1e+03 0.00086 1e+03 1 ++ 3 -0.06 -1.2 1.8 -1.6 0 0 0 0 0 -0.1 0.39 -1.4 0 0 5.1e+03 6.1e-06 1e+04 1 ++ 4 -0.06 -1.2 1.8 -1.6 0 0 0 0 0 -0.1 0.39 -1.4 0 0 5.1e+03 3.1e-10 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.45 -0.7 -1 0 0 0 0 0 -0.43 -0.12 0 0 5.6e+03 0.044 10 1 ++ 1 0.32 -1.1 -2.8 0 0 0 0 0 -0.13 0.31 0 0 5.4e+03 0.013 1e+02 1 ++ 2 0.38 -1.2 -3 0 0 0 0 0 -0.12 0.32 0 0 5.4e+03 0.00038 1e+03 1 ++ 3 0.38 -1.2 -3 0 0 0 0 0 -0.12 0.32 0 0 5.4e+03 3.7e-07 1e+03 1 ++ Considering neighbor 1/20 for current solution Considering neighbor 2/20 for current solution Attempt 19/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ asc_train_diff_ asc_train_diff_ b_time b_cost lambda_cost asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.41 -0.63 0.2 -0.0082 -1 -0.71 1 -0.28 -0.099 -0.21 -0.035 5.4e+03 0.037 10 1 ++ 1 -0.32 -1.1 0.73 0.33 -1.5 -1.3 -0.18 -0.35 0.22 -0.053 -0.48 5.2e+03 0.019 10 0.81 + 2 -0.48 -1.2 0.93 0.51 -1.5 -1.2 0.15 -0.35 0.25 -0.077 -0.59 5.2e+03 0.0052 1e+02 1.2 ++ 3 -0.48 -1.2 0.96 0.54 -1.6 -1.2 0.36 -0.32 0.24 -0.074 -0.57 5.2e+03 0.0012 1e+03 1.1 ++ 4 -0.47 -1.2 0.96 0.54 -1.6 -1.1 0.41 -0.31 0.24 -0.074 -0.56 5.2e+03 4.5e-05 1e+04 1 ++ 5 -0.47 -1.2 0.96 0.54 -1.6 -1.1 0.41 -0.31 0.24 -0.074 -0.56 5.2e+03 1.6e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ asc_train_diff_ b_time b_cost lambda_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.47 -0.7 0.44 -1 -0.64 1 0.0022 -0.28 -0.067 -0.19 5.3e+03 2.7 10 1.1 ++ 1 -0.47 -0.7 0.44 -1 -0.64 1 0.0022 -0.28 -0.067 -0.19 5.3e+03 2.7 1.3 -3.2 - 2 -0.12 -1 1.7 -1.4 -1.2 0.84 -0.0024 -0.33 0.21 -0.62 4.9e+03 0.7 13 1 ++ 3 -0.12 -1 1.7 -1.4 -1.2 0.84 -0.0024 -0.33 0.21 -0.62 4.9e+03 0.7 0.64 0.017 - 4 0.019 -1.2 2.2 -1.6 -1.4 0.2 -0.0063 -0.52 0.31 -1.1 4.8e+03 0.15 6.4 1.1 ++ 5 -0.071 -1.2 2.2 -1.6 -1.5 -0.045 -0.0066 -0.68 0.45 -1.8 4.8e+03 0.03 64 1 ++ 6 -0.071 -1.2 2.2 -1.6 -1.5 -0.036 -0.0066 -0.69 0.46 -2 4.8e+03 0.0014 6.4e+02 1 ++ 7 -0.071 -1.2 2.2 -1.6 -1.5 -0.036 -0.0066 -0.69 0.46 -2 4.8e+03 4.6e-06 6.4e+02 1 ++ Considering neighbor 1/20 for current solution *** New pareto solution: asc:MALE-GA;train_cost_catalog:boxcox;train_headway_catalog:with_headway;train_tt_catalog:log [9640.41233106946, np.float64(9708.61194008232), 10] Attempt 20/100 Considering neighbor 0/20 for current solution Attempt 21/100 Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.38 -0.79 -0.59 -0.93 -0.62 0.0095 5.4e+03 0.038 10 1.1 ++ 1 -0.11 -1.1 -0.98 -1 -0.63 0.34 5.3e+03 0.0068 1e+02 1.1 ++ 2 -0.075 -1.2 -1 -1.1 -0.63 0.36 5.3e+03 0.00023 1e+03 1 ++ 3 -0.075 -1.2 -1 -1.1 -0.63 0.36 5.3e+03 2.9e-07 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ b_time beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost lambda_cost beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_ma beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.67 -1 0 0 0 -0.83 1.1 0 0 -0.85 -0.14 0 0 5.6e+03 0.036 10 1 ++ 1 -0.67 -1 0 0 0 -0.83 1.1 0 0 -0.85 -0.14 0 0 5.6e+03 0.036 1 -4 - 2 -0.63 -1.4 0 0 0 -1.2 0.084 0 0 -1 0.19 0 0 5.5e+03 0.013 10 0.91 ++ 3 -0.8 -1.3 0 0 0 -1.2 0.16 0 0 -1.1 0.21 0 0 5.5e+03 0.00046 1e+02 1 ++ 4 -0.8 -1.3 0 0 0 -1.1 0.18 0 0 -1.1 0.21 0 0 5.5e+03 1.4e-05 1e+03 1 ++ 5 -0.8 -1.3 0 0 0 -1.1 0.18 0 0 -1.1 0.21 0 0 5.5e+03 4.4e-09 1e+03 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.33 -0.81 -0.63 -0.89 -0.52 -0.039 5.3e+03 0.043 10 1.1 ++ 1 0.038 -1.2 -1.2 -1 -0.47 0.28 5.2e+03 0.0093 1e+02 1.1 ++ 2 0.089 -1.2 -1.2 -1.1 -0.46 0.31 5.2e+03 0.00033 1e+03 1 ++ 3 0.089 -1.2 -1.2 -1.1 -0.46 0.31 5.2e+03 4.1e-07 1e+03 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_ma beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.77 -0.89 0 0 0 -0.88 0 0 -0.88 -0.05 0 0 5.5e+03 0.035 10 1 ++ 1 -0.75 -1.3 0 0 0 -0.94 0 0 -0.95 0.15 0 0 5.5e+03 0.0059 1e+02 1.1 ++ 2 -0.75 -1.3 0 0 0 -0.95 0 0 -0.95 0.14 0 0 5.5e+03 0.00018 1e+03 1 ++ 3 -0.75 -1.3 0 0 0 -0.95 0 0 -0.95 0.14 0 0 5.5e+03 1.5e-07 1e+03 1 ++ Considering neighbor 3/20 for current solution Considering neighbor 4/20 for current solution Attempt 22/100 Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost b_headway asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.18 -0.82 -0.63 -0.89 -0.0028 -0.55 -0.061 5.3e+03 2.5 10 1.1 ++ 1 0.29 -1.2 -1.1 -1 -0.0051 -0.56 0.28 5.2e+03 0.37 1e+02 1.1 ++ 2 0.37 -1.2 -1.2 -1.1 -0.0058 -0.58 0.31 5.2e+03 0.017 1e+03 1 ++ 3 0.38 -1.2 -1.2 -1.1 -0.0059 -0.58 0.31 5.2e+03 3.9e-05 1e+04 1 ++ 4 0.38 -1.2 -1.2 -1.1 -0.0059 -0.58 0.31 5.2e+03 6.4e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost lambda_cost asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.38 -0.76 -0.61 -0.87 2 -0.72 0.11 5.6e+03 0.068 10 0.94 ++ 1 -0.38 -0.76 -0.61 -0.87 2 -0.72 0.11 5.6e+03 0.068 4.2 -1.4e+05 - 2 -0.38 -0.76 -0.61 -0.87 2 -0.72 0.11 5.6e+03 0.068 2.1 -1.3e+02 - 3 -0.38 -0.76 -0.61 -0.87 2 -0.72 0.11 5.6e+03 0.068 1.1 -9.9 - 4 -0.38 -0.76 -0.61 -0.87 2 -0.72 0.11 5.6e+03 0.068 0.53 -0.41 - 5 -0.077 -0.94 -1.1 -0.59 1.8 -0.53 0.38 5.3e+03 0.0089 5.3 1.1 ++ 6 -0.077 -0.94 -1.1 -0.59 1.8 -0.53 0.38 5.3e+03 0.0089 2.6 -6e+02 - 7 -0.077 -0.94 -1.1 -0.59 1.8 -0.53 0.38 5.3e+03 0.0089 1.3 -5.5 - 8 0.33 -1.4 -1.1 -1.1 0.44 -0.54 0.33 5.3e+03 0.021 1.3 0.67 + 9 0.014 -1.2 -1.1 -1.1 0.61 -0.6 0.33 5.3e+03 0.00094 13 1 ++ 10 0.014 -1.2 -1.1 -1.1 0.61 -0.6 0.33 5.3e+03 4.5e-06 13 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. asc_train_ref asc_train_diff_ asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.51 -0.8 1 -0.6 -0.88 -0.46 -0.15 -0.21 5.1e+03 0.045 10 1.1 ++ 1 -0.54 -0.96 1.7 -1.1 -1.1 -0.6 0.36 -0.37 5e+03 0.012 1e+02 1.1 ++ 2 -0.53 -1.1 1.9 -1.2 -1.1 -0.61 0.41 -0.41 4.9e+03 0.0007 1e+03 1 ++ 3 -0.53 -1.1 1.9 -1.2 -1.1 -0.61 0.41 -0.41 4.9e+03 4.3e-06 1e+03 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ asc_train_diff_ b_time b_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.47 -0.7 0.44 -1 -0.77 0.0019 -0.27 -0.061 -0.18 5.2e+03 2.6 10 1.1 ++ 1 -0.004 -1 2 -1.6 -1 -0.0044 -0.46 0.32 -0.32 4.9e+03 0.99 1e+02 1 ++ 2 0.1 -1.2 2 -1.7 -1.1 -0.0064 -0.52 0.37 -0.39 4.9e+03 0.083 1e+03 1.1 ++ 3 0.11 -1.2 2.1 -1.7 -1.1 -0.0066 -0.52 0.37 -0.39 4.9e+03 0.00032 1e+04 1 ++ 4 0.11 -1.2 2.1 -1.7 -1.1 -0.0066 -0.52 0.37 -0.39 4.9e+03 6.9e-06 1e+05 1 ++ 5 0.11 -1.2 2.1 -1.7 -1.1 -0.0066 -0.52 0.37 -0.39 4.9e+03 1e-07 1e+05 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. asc_train_ref asc_train_diff_ b_time b_cost beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.083 -0.77 -0.62 0 0 0 -0.0027 0 0 -0.47 0.023 0 0 5.6e+03 2.9 10 1.1 ++ 1 0.34 -1.1 -1.1 0 0 0 -0.005 0 0 -0.38 0.33 0 0 5.4e+03 0.37 1e+02 1.1 ++ 2 0.41 -1.2 -1.1 0 0 0 -0.0057 0 0 -0.39 0.32 0 0 5.4e+03 0.018 1e+03 1 ++ 3 0.41 -1.2 -1.1 0 0 0 -0.0057 0 0 -0.39 0.32 0 0 5.4e+03 3.6e-05 1e+04 1 ++ 4 0.41 -1.2 -1.1 0 0 0 -0.0057 0 0 -0.39 0.32 0 0 5.4e+03 1.4e-10 1e+04 1 ++ Considering neighbor 4/20 for current solution Considering neighbor 5/20 for current solution Attempt 23/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ asc_train_diff_ b_time b_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.58 -0.83 0.7 -1 -0.96 -0.00091 -0.53 -0.2 -0.22 5.2e+03 2.6 10 1.1 ++ 1 -0.099 -0.98 1.8 -2.8 -1 -0.005 -0.54 0.34 -0.38 4.9e+03 0.69 1e+02 1.1 ++ 2 0.04 -1.1 1.9 -3.2 -1.1 -0.0066 -0.58 0.41 -0.42 4.9e+03 0.057 1e+03 1.1 ++ 3 0.049 -1.2 2 -3.2 -1.1 -0.0068 -0.59 0.41 -0.43 4.9e+03 0.00035 1e+04 1 ++ 4 0.049 -1.2 2 -3.2 -1.1 -0.0068 -0.59 0.41 -0.43 4.9e+03 9.9e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.44 -0.59 0.47 -1 -0.76 -0.34 -0.17 -0.18 5.2e+03 0.044 10 1 ++ 1 -0.21 -1 2 -1.6 -1 -0.36 0.33 -0.35 4.9e+03 0.018 1e+02 1 ++ 2 -0.2 -1.2 2 -1.7 -1.1 -0.39 0.37 -0.42 4.9e+03 0.0011 1e+03 1 ++ 3 -0.2 -1.2 2 -1.7 -1.1 -0.39 0.38 -0.42 4.9e+03 8.5e-06 1e+04 1 ++ 4 -0.2 -1.2 2 -1.7 -1.1 -0.39 0.38 -0.42 4.9e+03 5.5e-10 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 20 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. Function Relgrad Radius Rho 0 5.6e+03 0.044 10 1.1 ++ 1 5.4e+03 0.01 1e+02 1.1 ++ 2 5.4e+03 0.00066 1e+03 1 ++ 3 5.4e+03 3.5e-06 1e+03 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_ma asc_car_diff_wi beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.87 -0.94 1 0 0 0 -0.89 0 0 -0.7 -0.27 -0.19 0 0 5.4e+03 0.041 10 1.1 ++ 1 -1.3 -1.1 1.9 0 0 0 -0.99 0 0 -1.1 0.25 -0.15 0 0 5.2e+03 0.012 1e+02 1.1 ++ 2 -1.4 -1.2 2 0 0 0 -1 0 0 -1.1 0.25 -0.16 0 0 5.2e+03 0.0008 1e+03 1 ++ 3 -1.4 -1.2 2 0 0 0 -1 0 0 -1.1 0.25 -0.16 0 0 5.2e+03 4.2e-06 1e+03 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.54 -0.74 0.8 -1 0 0 0 0 0 -0.44 -0.14 -0.33 0 0 5.4e+03 0.049 10 1 ++ 1 -0.17 -0.96 1.6 -2.8 0 0 0 0 0 -0.15 0.39 -1.3 0 0 5.1e+03 0.018 1e+02 1.1 ++ 2 -0.14 -1.1 1.7 -3 0 0 0 0 0 -0.16 0.43 -1.5 0 0 5.1e+03 0.00093 1e+03 1 ++ 3 -0.14 -1.1 1.7 -3 0 0 0 0 0 -0.16 0.43 -1.5 0 0 5.1e+03 4.8e-06 1e+03 1 ++ Considering neighbor 4/20 for current solution Considering neighbor 5/20 for current solution Attempt 24/100 Considering neighbor 0/20 for current solution Attempt 25/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ asc_train_diff_ asc_train_diff_ b_time lambda_tt b_cost lambda_cost asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.45 -0.73 0.3 -0.01 -0.94 2 -1 1 -0.37 -0.15 -0.27 -0.048 5.8e+03 0.11 1 0.64 + 1 -0.58 -1.3 1.3 0.31 -1.7 1 -1.7 0.44 -0.95 0.51 0.37 -0.41 5.3e+03 0.045 10 0.94 ++ 2 -0.33 -1.1 0.91 0.51 -1.8 0.51 -1 0.5 -0.2 0.3 -0.12 -0.57 5.2e+03 0.014 1e+02 1 ++ 3 -0.48 -1.1 0.95 0.52 -1.6 0.41 -1.1 0.57 -0.36 0.29 -0.059 -0.52 5.1e+03 0.0015 1e+03 1 ++ 4 -0.48 -1.1 0.95 0.52 -1.6 0.38 -1.1 0.53 -0.35 0.29 -0.061 -0.52 5.1e+03 5.8e-05 1e+04 1 ++ 5 -0.48 -1.1 0.95 0.52 -1.6 0.38 -1.1 0.53 -0.35 0.29 -0.061 -0.52 5.1e+03 2.4e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 lambda_tt b_cost asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.45 -0.73 0.31 -0.0099 -0.93 2 -0.96 -0.36 -0.14 -0.27 -0.049 5.8e+03 0.12 1 0.6 + 1 -0.96 -1.7 1.2 0.13 0.057 2.1 -0.99 -0.87 0.3 0.056 -0.32 5.7e+03 0.33 1 0.28 + 2 -0.96 -1.7 1.2 0.13 0.057 2.1 -0.99 -0.87 0.3 0.056 -0.32 5.7e+03 0.33 0.5 -2 - 3 -0.96 -1.7 1.2 0.13 0.057 2.1 -0.99 -0.87 0.3 0.056 -0.32 5.7e+03 0.33 0.25 -0.2 - 4 -1.2 -1.8 0.95 0.13 -0.19 2 -0.96 -1 0.12 -0.0082 -0.33 5.5e+03 0.04 0.25 0.74 + 5 -1.1 -1.5 0.99 0.15 -0.24 1.9 -1.1 -0.92 0.21 0.052 -0.33 5.4e+03 0.011 2.5 0.97 ++ 6 -1.1 -1.5 0.99 0.15 -0.24 1.9 -1.1 -0.92 0.21 0.052 -0.33 5.4e+03 0.011 1.2 -0.032 - 7 -1.3 -1 0.76 0.23 -0.71 0.63 -1.1 -0.88 0.19 0.022 -0.35 5.3e+03 0.026 1.2 0.72 + 8 -0.56 -1.1 0.97 0.59 -1.5 0.12 -1.1 -0.38 0.31 -0.066 -0.59 5.2e+03 0.0056 12 0.93 ++ 9 -0.51 -1.1 0.95 0.51 -1.6 0.35 -1.1 -0.35 0.31 -0.073 -0.62 5.2e+03 0.0027 12 0.86 + 10 -0.54 -1.1 0.95 0.51 -1.5 0.32 -1.1 -0.37 0.31 -0.071 -0.62 5.2e+03 6.7e-05 1.2e+02 1 ++ 11 -0.54 -1.1 0.95 0.51 -1.5 0.32 -1.1 -0.37 0.31 -0.071 -0.62 5.2e+03 1.1e-07 1.2e+02 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 lambda_tt b_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.57 -0.95 0.17 -0.0032 -0.94 1.9 -1 0.0067 -0.17 0.09 -0.12 -0.049 5.7e+03 2.4 1 0.75 + 1 -0.34 -1.3 1.2 0.25 -1.6 0.89 -1.1 -0.0025 -0.79 0.55 0.25 -0.39 5.2e+03 0.86 10 1 ++ 2 -0.091 -1.1 0.94 0.51 -1.8 0.39 -1.1 -0.0059 -0.38 0.33 -0.095 -0.66 5.2e+03 0.014 1e+02 1.1 ++ 3 -0.26 -1.1 0.96 0.5 -1.5 0.35 -1.1 -0.0059 -0.49 0.31 -0.068 -0.62 5.1e+03 0.0012 1e+03 1 ++ 4 -0.26 -1.1 0.96 0.5 -1.5 0.32 -1.1 -0.0059 -0.48 0.31 -0.069 -0.61 5.1e+03 5.7e-05 1e+04 0.99 ++ 5 -0.26 -1.1 0.96 0.5 -1.5 0.32 -1.1 -0.0059 -0.48 0.31 -0.069 -0.61 5.1e+03 1.5e-07 1e+04 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 26/100 Considering neighbor 0/20 for current solution Attempt 27/100 Considering neighbor 0/20 for current solution Attempt 28/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.53 0.32 -1 0 0 0 -0.0036 0 0 -0.41 -0.16 0 0 5.6e+03 2.6 10 1 ++ 1 -0.53 2 -1.6 0 0 0 -0.0051 0 0 0.14 -1 0 0 5.2e+03 0.87 1e+02 0.97 ++ 2 -0.61 1.9 -1.6 0 0 0 -0.0059 0 0 0.11 -1.3 0 0 5.2e+03 0.039 1e+03 1 ++ 3 -0.62 1.9 -1.6 0 0 0 -0.006 0 0 0.11 -1.3 0 0 5.2e+03 0.00019 1e+04 1 ++ 4 -0.62 1.9 -1.6 0 0 0 -0.006 0 0 0.11 -1.3 0 0 5.2e+03 4.2e-09 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.53 0.32 -1 0 0 0 -0.0036 0 0 -0.41 -0.16 0 0 5.6e+03 2.6 10 1 ++ 1 -0.53 2 -1.6 0 0 0 -0.0051 0 0 0.14 -1 0 0 5.2e+03 0.87 1e+02 0.97 ++ 2 -0.61 1.9 -1.6 0 0 0 -0.0059 0 0 0.11 -1.3 0 0 5.2e+03 0.039 1e+03 1 ++ 3 -0.62 1.9 -1.6 0 0 0 -0.006 0 0 0.11 -1.3 0 0 5.2e+03 0.00019 1e+04 1 ++ 4 -0.62 1.9 -1.6 0 0 0 -0.006 0 0 0.11 -1.3 0 0 5.2e+03 4.2e-09 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_on asc_car_diff_se beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.65 0.022 -0.01 -1 0 0 0 0 0 -0.22 -0.2 -0.029 0 0 5.7e+03 0.045 10 1 ++ 1 -0.91 0.8 0.63 -1.5 0 0 0 0 0 0.25 -0.088 -0.72 0 0 5.5e+03 0.009 1e+02 1.1 ++ 2 -1.2 1.1 0.9 -1.6 0 0 0 0 0 0.24 -0.083 -0.77 0 0 5.5e+03 0.001 1e+03 1.1 ++ 3 -1.2 1.1 0.94 -1.6 0 0 0 0 0 0.24 -0.084 -0.77 0 0 5.5e+03 1.8e-05 1e+04 1 ++ 4 -1.2 1.1 0.94 -1.6 0 0 0 0 0 0.24 -0.084 -0.77 0 0 5.5e+03 5e-09 1e+04 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.71 0.23 -1 0 0 0 0 0 -0.31 -0.14 0 0 5.6e+03 0.044 10 1 ++ 1 -0.77 2.1 -1.6 0 0 0 0 0 0.24 -1 0 0 5.3e+03 0.023 1e+02 0.93 ++ 2 -0.88 1.9 -1.6 0 0 0 0 0 0.23 -1.3 0 0 5.2e+03 0.00045 1e+03 1 ++ 3 -0.88 1.9 -1.6 0 0 0 0 0 0.23 -1.3 0 0 5.2e+03 1.6e-06 1e+03 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ asc_train_diff_ b_time b_cost lambda_cost b_headway asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.53 -0.019 -0.005 -1 -0.46 1 -0.0034 -0.36 -0.21 -0.03 5.5e+03 2.4 10 1 ++ 1 -0.87 0.83 0.79 -1.5 -1.1 -0.38 -0.005 -0.15 -0.079 -0.65 5.3e+03 0.63 10 0.88 + 2 -1.2 1.1 0.97 -1.5 -1.4 0.29 -0.0055 -0.29 -0.069 -0.7 5.3e+03 0.046 1e+02 0.91 ++ 3 -1.2 1.2 0.99 -1.5 -1.1 0.36 -0.0055 -0.19 -0.072 -0.66 5.3e+03 0.0008 1e+03 0.97 ++ 4 -1.2 1.2 1 -1.6 -1.1 0.4 -0.0055 -0.2 -0.069 -0.65 5.3e+03 0.00022 1e+04 0.97 ++ 5 -1.2 1.2 1 -1.6 -1.1 0.4 -0.0055 -0.2 -0.069 -0.65 5.3e+03 3.2e-07 1e+04 1 ++ Considering neighbor 4/20 for current solution Considering neighbor 5/20 for current solution Attempt 29/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.22 -0.77 -0.62 0 0 0 0 0 -0.42 0.022 0 0 5.6e+03 0.038 10 1.1 ++ 1 0.1 -1.1 -1.1 0 0 0 0 0 -0.29 0.33 0 0 5.5e+03 0.0078 1e+02 1.1 ++ 2 0.13 -1.2 -1.1 0 0 0 0 0 -0.28 0.33 0 0 5.5e+03 0.00024 1e+03 1 ++ 3 0.13 -1.2 -1.1 0 0 0 0 0 -0.28 0.33 0 0 5.5e+03 3.2e-07 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ref asc_train_diff_ asc_train_diff_ b_time b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_on asc_car_diff_se beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -1 0.066 -0.017 -1 0 0 0 0 0 -0.39 -0.27 -0.046 0 0 5.7e+03 0.041 10 1 ++ 1 -0.97 0.8 0.62 -2.8 0 0 0 0 0 0.19 -0.051 -0.68 0 0 5.5e+03 0.014 1e+02 1.1 ++ 2 -1.2 1.1 0.85 -3 0 0 0 0 0 0.22 -0.075 -0.76 0 0 5.5e+03 0.00099 1e+03 1.1 ++ 3 -1.2 1.1 0.88 -3 0 0 0 0 0 0.22 -0.076 -0.77 0 0 5.5e+03 1.6e-05 1e+04 1 ++ 4 -1.2 1.1 0.88 -3 0 0 0 0 0 0.22 -0.076 -0.77 0 0 5.5e+03 4.3e-09 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. Function Relgrad Radius Rho 0 5.5e+03 0.039 10 1.1 ++ 1 5.4e+03 0.009 1e+02 1.1 ++ 2 5.4e+03 0.00054 1e+03 1.1 ++ 3 5.4e+03 4.8e-06 1e+03 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. Function Relgrad Radius Rho 0 5.6e+03 0.038 10 1.1 ++ 1 5.3e+03 0.013 1e+02 1.1 ++ 2 5.3e+03 0.0006 1e+03 1 ++ 3 5.3e+03 3.1e-06 1e+03 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.64 -0.82 0.18 -0.02 -0.9 -1 -0.41 -0.18 -0.25 -0.04 5.4e+03 0.034 10 1.1 ++ 1 -0.34 -1.1 0.73 0.35 -2.9 -1 -0.39 0.28 0.11 -0.085 5.1e+03 0.016 1e+02 1.1 ++ 2 -0.41 -1.1 0.93 0.52 -3.3 -1.1 -0.37 0.31 0.081 -0.14 5.1e+03 0.0011 1e+03 1 ++ 3 -0.43 -1.1 0.95 0.54 -3.3 -1.1 -0.37 0.32 0.08 -0.14 5.1e+03 7.5e-06 1e+04 1 ++ 4 -0.43 -1.1 0.95 0.54 -3.3 -1.1 -0.37 0.32 0.08 -0.14 5.1e+03 8.6e-10 1e+04 1 ++ Considering neighbor 4/20 for current solution Considering neighbor 5/20 for current solution Attempt 30/100 Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. Function Relgrad Radius Rho 0 5.8e+03 0.039 10 1.1 ++ 1 5.3e+03 0.058 1e+02 0.98 ++ 2 5.3e+03 0.0041 1e+03 1 ++ 3 5.3e+03 0.00015 1e+04 1 ++ 4 5.3e+03 1.7e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. Function Relgrad Radius Rho 0 5.9e+03 0.04 10 1.1 ++ 1 5.9e+03 0.04 5 -1.1e+07 - 2 5.9e+03 0.04 2.5 -1.8e+02 - 3 5.9e+03 0.04 1.2 0.051 - 4 5.4e+03 0.043 12 1.1 ++ 5 5.4e+03 0.043 2.7 -3.1e+03 - 6 5.4e+03 0.043 1.4 -17 - 7 5.3e+03 0.057 1.4 0.48 + 8 5.2e+03 0.0044 14 0.91 ++ 9 5.2e+03 0.0019 14 0.89 + 10 5.2e+03 3.7e-05 1.4e+02 1 ++ 11 5.2e+03 5e-08 1.4e+02 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost lambda_cost b_headway beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_ma beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.57 -0.94 0 0 0 -0.84 1.3 -0.0031 0 0 -1 -0.046 0 0 5.6e+03 2.6 10 1 ++ 1 -0.57 -0.94 0 0 0 -0.84 1.3 -0.0031 0 0 -1 -0.046 0 0 5.6e+03 2.6 2.1 -2.1e+02 - 2 -0.57 -0.94 0 0 0 -0.84 1.3 -0.0031 0 0 -1 -0.046 0 0 5.6e+03 2.6 1 -2.6 - 3 -0.39 -1.5 0 0 0 -1.3 0.24 -0.0064 0 0 -1.3 0.078 0 0 5.5e+03 0.58 10 1 ++ 4 -0.51 -1.4 0 0 0 -1.1 0.19 -0.0059 0 0 -1.2 0.22 0 0 5.5e+03 0.022 1e+02 0.97 ++ 5 -0.52 -1.3 0 0 0 -1.1 0.19 -0.0059 0 0 -1.2 0.21 0 0 5.5e+03 5.2e-05 1e+03 1 ++ 6 -0.52 -1.3 0 0 0 -1.1 0.19 -0.0059 0 0 -1.2 0.21 0 0 5.5e+03 1.4e-09 1e+03 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 31/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_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_ b_time beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost lambda_cost beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_ma beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.67 -1 0 0 0 -0.83 1.1 0 0 -0.85 -0.14 0 0 5.6e+03 0.036 10 1 ++ 1 -0.67 -1 0 0 0 -0.83 1.1 0 0 -0.85 -0.14 0 0 5.6e+03 0.036 1 -4 - 2 -0.63 -1.4 0 0 0 -1.2 0.084 0 0 -1 0.19 0 0 5.5e+03 0.013 10 0.91 ++ 3 -0.8 -1.3 0 0 0 -1.2 0.16 0 0 -1.1 0.21 0 0 5.5e+03 0.00046 1e+02 1 ++ 4 -0.8 -1.3 0 0 0 -1.1 0.18 0 0 -1.1 0.21 0 0 5.5e+03 1.4e-05 1e+03 1 ++ 5 -0.8 -1.3 0 0 0 -1.1 0.18 0 0 -1.1 0.21 0 0 5.5e+03 4.4e-09 1e+03 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 32/100 Considering neighbor 0/20 for current solution Attempt 33/100 Considering neighbor 0/20 for current solution Attempt 34/100 Considering neighbor 0/20 for current solution Attempt 35/100 Biogeme parameters read from biogeme.toml. Model with 21 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. Function Relgrad Radius Rho 0 5.6e+03 3.3 10 1.1 ++ 1 5.4e+03 0.55 1e+02 1.1 ++ 2 5.4e+03 0.048 1e+03 1 ++ 3 5.4e+03 0.00034 1e+04 1 ++ 4 5.4e+03 1.7e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. asc_train_ref asc_train_diff_ asc_train_diff_ b_time b_cost beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.53 -0.81 0.78 -1 0 0 0 0.00034 0 0 -0.42 -0.079 -0.32 0 0 5.4e+03 3.2 10 1.1 ++ 1 0.04 -0.98 1.6 -2.8 0 0 0 -0.0045 0 0 -0.25 0.38 -1.2 0 0 5.1e+03 0.64 1e+02 1.1 ++ 2 0.16 -1.1 1.7 -3 0 0 0 -0.0063 0 0 -0.29 0.42 -1.5 0 0 5.1e+03 0.059 1e+03 1.1 ++ 3 0.17 -1.1 1.8 -3 0 0 0 -0.0065 0 0 -0.29 0.43 -1.5 0 0 5.1e+03 0.00056 1e+04 1 ++ 4 0.17 -1.1 1.8 -3 0 0 0 -0.0065 0 0 -0.29 0.43 -1.5 0 0 5.1e+03 4.8e-08 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 21 unknown parameters [max: 50] *** Estimate b21_multiple_models_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. Function Relgrad Radius Rho 0 5.6e+03 3.3 10 1.1 ++ 1 5.4e+03 0.55 1e+02 1.1 ++ 2 5.4e+03 0.048 1e+03 1 ++ 3 5.4e+03 0.00034 1e+04 1 ++ 4 5.4e+03 1.7e-08 1e+04 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 36/100 Considering neighbor 0/20 for current solution Attempt 37/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost lambda_cost b_headway asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -0.83 0.17 0.0037 1 -0.76 -0.99 1 -0.0043 -0.48 -0.17 -0.071 -0.42 5.2e+03 2.5 10 1.1 ++ 1 -0.83 0.17 0.0037 1 -0.76 -0.99 1 -0.0043 -0.48 -0.17 -0.071 -0.42 5.2e+03 2.5 0.82 0.069 - 2 -1.1 0.57 0.066 1.8 -1.2 -1.2 0.6 -0.0075 -0.4 -0.018 -0.14 -0.81 5e+03 0.69 8.2 1.1 ++ 3 -1.6 0.69 0.52 1.9 -1 -1.6 -0.016 -0.0064 -0.56 0.11 -0.33 -1.7 5e+03 0.033 8.2 0.9 + 4 -1.6 0.71 0.55 1.9 -1 -1.5 0.081 -0.0063 -0.55 0.12 -0.39 -1.8 5e+03 0.00094 82 1.1 ++ 5 -1.6 0.71 0.55 1.9 -1 -1.5 0.11 -0.0063 -0.54 0.11 -0.39 -1.8 5e+03 4.2e-05 8.2e+02 1 ++ 6 -1.6 0.71 0.55 1.9 -1 -1.5 0.11 -0.0063 -0.54 0.11 -0.39 -1.8 5e+03 1.3e-07 8.2e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_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 b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_on asc_car_diff_se beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.65 0.022 -0.01 -1 0 0 0 0 0 -0.22 -0.2 -0.029 0 0 5.7e+03 0.045 10 1 ++ 1 -0.91 0.8 0.63 -1.5 0 0 0 0 0 0.25 -0.088 -0.72 0 0 5.5e+03 0.009 1e+02 1.1 ++ 2 -1.2 1.1 0.9 -1.6 0 0 0 0 0 0.24 -0.083 -0.77 0 0 5.5e+03 0.001 1e+03 1.1 ++ 3 -1.2 1.1 0.94 -1.6 0 0 0 0 0 0.24 -0.084 -0.77 0 0 5.5e+03 1.8e-05 1e+04 1 ++ 4 -1.2 1.1 0.94 -1.6 0 0 0 0 0 0.24 -0.084 -0.77 0 0 5.5e+03 5e-09 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b21_multiple_models_000115 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 beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_on asc_car_diff_se beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.97 0.51 0.33 -0.63 0 0 0 -0.0026 0 0 -0.47 0.1 -0.43 0 0 5.6e+03 2.7 10 1.1 ++ 1 -1 0.91 0.71 -1.1 0 0 0 -0.0047 0 0 -0.042 -0.054 -0.68 0 0 5.5e+03 0.35 1e+02 1.1 ++ 2 -1.2 1.1 0.89 -1.1 0 0 0 -0.0053 0 0 -0.05 -0.044 -0.68 0 0 5.5e+03 0.026 1e+03 1 ++ 3 -1.2 1.1 0.91 -1.1 0 0 0 -0.0054 0 0 -0.05 -0.044 -0.68 0 0 5.5e+03 0.00018 1e+04 1 ++ 4 -1.2 1.1 0.91 -1.1 0 0 0 -0.0054 0 0 -0.05 -0.044 -0.68 0 0 5.5e+03 1.1e-08 1e+04 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 38/100 Biogeme parameters read from biogeme.toml. Model with 5 unknown parameters [max: 50] *** Estimate b21_multiple_models_000116 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 b_headway asc_car Function Relgrad Radius Rho 0 -0.93 -1 -0.68 -0.0036 -0.79 5.5e+03 2.3 10 1 ++ 1 -0.36 -3 -0.97 -0.0044 -0.11 5.3e+03 0.12 1e+02 1.1 ++ 2 -0.25 -3.3 -1.1 -0.0052 -0.11 5.3e+03 0.013 1e+03 1 ++ 3 -0.23 -3.4 -1.1 -0.0053 -0.11 5.3e+03 0.00049 1e+04 1 ++ 4 -0.23 -3.4 -1.1 -0.0053 -0.11 5.3e+03 6.8e-05 1e+05 1 ++ 5 -0.23 -3.4 -1.1 -0.0053 -0.11 5.3e+03 2.6e-06 1e+05 1 ++ Considering neighbor 0/20 for current solution *** New pareto solution: asc:no_seg;train_cost_catalog:linear;train_headway_catalog:with_headway;train_tt_catalog:sqrt [10562.742717771165, np.float64(10596.842522277595), 5] Attempt 39/100 Considering neighbor 0/20 for current solution Attempt 40/100 Biogeme parameters read from biogeme.toml. Model with 22 unknown parameters [max: 50] *** Estimate b21_multiple_models_000117 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 5.7e+03 0.039 10 1 ++ 1 5.6e+03 0.0083 1e+02 1.1 ++ 2 5.6e+03 0.00067 1e+03 1 ++ 3 5.6e+03 5.4e-06 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 5 unknown parameters [max: 50] *** Estimate b21_multiple_models_000118 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_tt b_cost asc_car Function Relgrad Radius Rho 0 -0.71 -1 1.7 -0.82 -0.5 5.6e+03 0.058 1 0.77 + 1 -0.77 -1.7 0.69 -1.3 -0.35 5.4e+03 0.049 10 1 ++ 2 -0.47 -1.7 0.53 -1 0.017 5.3e+03 0.002 1e+02 0.96 ++ 3 -0.48 -1.7 0.51 -1.1 -0.0043 5.3e+03 1.3e-05 1e+03 1 ++ 4 -0.48 -1.7 0.51 -1.1 -0.0043 5.3e+03 1.8e-09 1e+03 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000119 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 6e+03 0.12 1 0.57 + 1 6e+03 0.12 0.5 -0.17 - 2 5.6e+03 0.022 5 0.91 ++ 3 5.6e+03 0.022 2.5 -12 - 4 5.6e+03 0.022 1.2 -0.22 - 5 5.4e+03 0.037 1.2 0.85 + 6 5.3e+03 0.0087 1.2 0.89 + 7 5.3e+03 0.00037 12 0.99 ++ 8 5.3e+03 2.9e-06 12 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000120 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 5.6e+03 0.038 10 1 ++ 1 5.6e+03 0.038 0.95 -1.8 - 2 5.4e+03 0.021 9.5 0.92 ++ 3 5.4e+03 0.00087 95 0.97 ++ 4 5.4e+03 2.2e-05 9.5e+02 0.99 ++ 5 5.4e+03 3.2e-08 9.5e+02 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_000121 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_tt b_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.5 -0.79 0.093 -0.0049 -0.88 1.6 -1 0.0035 -0.21 0.00042 -0.13 -0.038 5.4e+03 2.2 1 0.9 + 1 -0.18 -1.2 1.1 0.056 -1.5 0.76 -1.1 -0.0049 -0.46 0.21 0.093 -0.099 5.1e+03 0.88 10 1 ++ 2 -0.051 -1.1 0.96 0.57 -1.8 0.39 -1.1 -0.0058 -0.41 0.3 0.068 -0.17 5.1e+03 0.034 1e+02 0.91 ++ 3 -0.12 -1.1 0.96 0.53 -1.7 0.44 -1.1 -0.0059 -0.47 0.31 0.077 -0.14 5.1e+03 0.00022 1e+03 1 ++ 4 -0.12 -1.1 0.96 0.53 -1.7 0.44 -1.1 -0.0059 -0.47 0.31 0.077 -0.14 5.1e+03 7.1e-07 1e+03 1 ++ Considering neighbor 4/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000122 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 lambda_cost asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.8 -0.64 0.51 0.19 -0.59 -0.84 2 -0.84 0.15 0.14 -0.38 5.5e+03 0.065 10 0.95 ++ 1 -0.8 -0.64 0.51 0.19 -0.59 -0.84 2 -0.84 0.15 0.14 -0.38 5.5e+03 0.065 5 -2.4e+06 - 2 -0.8 -0.64 0.51 0.19 -0.59 -0.84 2 -0.84 0.15 0.14 -0.38 5.5e+03 0.065 2.5 -1.2e+02 - 3 -0.8 -0.64 0.51 0.19 -0.59 -0.84 2 -0.84 0.15 0.14 -0.38 5.5e+03 0.065 1.2 -2.6 - 4 -0.039 -0.91 0.37 0.87 -1.6 -1.6 0.75 0.11 -0.34 -0.00021 -0.18 5.3e+03 0.037 1.2 0.68 + 5 -0.71 -1 0.85 0.53 -1.1 -0.97 0.71 -0.56 0.32 -0.013 -0.44 5.2e+03 0.0065 12 0.95 ++ 6 -0.78 -1.1 0.95 0.56 -1.1 -1.1 0.56 -0.58 0.31 -0.016 -0.41 5.2e+03 0.00051 1.2e+02 0.97 ++ 7 -0.78 -1.1 0.96 0.56 -1.1 -1.1 0.59 -0.57 0.31 -0.016 -0.41 5.2e+03 1.9e-05 1.2e+03 1 ++ 8 -0.78 -1.1 0.96 0.56 -1.1 -1.1 0.59 -0.57 0.31 -0.016 -0.41 5.2e+03 1.5e-09 1.2e+03 1 ++ Considering neighbor 5/20 for current solution Biogeme parameters read from biogeme.toml. Model with 5 unknown parameters [max: 50] *** Estimate b21_multiple_models_000123 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 lambda_cost asc_car Function Relgrad Radius Rho 0 -0.93 -0.64 -0.85 2 -0.56 5.7e+03 0.067 10 0.92 ++ 1 -0.93 -0.64 -0.85 2 -0.56 5.7e+03 0.067 4.1 -1.3e+05 - 2 -0.93 -0.64 -0.85 2 -0.56 5.7e+03 0.067 2.1 -1.2e+02 - 3 -0.93 -0.64 -0.85 2 -0.56 5.7e+03 0.067 1 -9.9 - 4 -0.93 -0.64 -0.85 2 -0.56 5.7e+03 0.067 0.52 -0.53 - 5 -0.7 -1.2 -0.62 1.7 -0.18 5.5e+03 0.0091 5.2 1.1 ++ 6 -0.7 -1.2 -0.62 1.7 -0.18 5.5e+03 0.0091 2.5 -5.6e+02 - 7 -0.7 -1.2 -0.62 1.7 -0.18 5.5e+03 0.0091 1.3 -5.7 - 8 -0.56 -1.3 -1.2 0.46 -0.14 5.4e+03 0.012 1.3 0.57 + 9 -0.78 -1.2 -1.1 0.6 -0.26 5.4e+03 0.00052 13 1 ++ 10 -0.78 -1.2 -1.1 0.63 -0.26 5.4e+03 2.1e-05 1.3e+02 1 ++ 11 -0.78 -1.2 -1.1 0.63 -0.26 5.4e+03 1e-08 1.3e+02 1 ++ Considering neighbor 6/20 for current solution Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_000124 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 lambda_cost asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.45 -0.68 0.7 -0.72 -1 1 -0.41 -0.18 -0.32 5.2e+03 0.04 10 1.1 ++ 1 -0.72 -0.91 1.9 -0.99 -1.8 -0.33 -0.76 0.35 -1.5 5e+03 0.05 10 0.78 + 2 -0.78 -1.1 2 -0.98 -1.4 -0.25 -0.78 0.48 -1.9 4.9e+03 0.0018 1e+02 1.1 ++ 3 -0.73 -1.1 2 -1 -1.5 0.1 -0.79 0.47 -1.9 4.9e+03 0.005 1e+03 0.91 ++ 4 -0.72 -1.1 2 -1 -1.5 0.1 -0.77 0.46 -1.9 4.9e+03 6e-05 1e+04 0.99 ++ 5 -0.72 -1.1 2 -1 -1.5 0.1 -0.77 0.46 -1.9 4.9e+03 1.9e-08 1e+04 1 ++ Considering neighbor 7/20 for current solution Considering neighbor 8/20 for current solution Attempt 41/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_000125 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 beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.93 0.5 -1 0 0 0 -0.0031 0 0 -0.65 -0.25 0 0 5.6e+03 2.7 10 1 ++ 1 -0.6 1.8 -2.8 0 0 0 -0.005 0 0 0.11 -1.1 0 0 5.2e+03 0.68 1e+02 1 ++ 2 -0.63 1.8 -3 0 0 0 -0.0059 0 0 0.094 -1.4 0 0 5.2e+03 0.036 1e+03 1 ++ 3 -0.63 1.8 -3 0 0 0 -0.006 0 0 0.094 -1.4 0 0 5.2e+03 0.00017 1e+04 1 ++ 4 -0.63 1.8 -3 0 0 0 -0.006 0 0 0.094 -1.4 0 0 5.2e+03 3.4e-09 1e+04 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 42/100 Considering neighbor 0/20 for current solution Attempt 43/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b21_multiple_models_000126 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 beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_on asc_car_diff_se beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.52 0.052 -0.0022 -1 0 0 0 -0.0028 0 0 -0.25 -0.14 -0.034 0 0 5.6e+03 2.5 10 1 ++ 1 -0.7 0.81 0.63 -1.5 0 0 0 -0.0047 0 0 0.15 -0.089 -0.71 0 0 5.5e+03 0.44 1e+02 1.1 ++ 2 -0.94 1.1 0.9 -1.6 0 0 0 -0.0053 0 0 0.13 -0.081 -0.76 0 0 5.5e+03 0.05 1e+03 1.1 ++ 3 -0.98 1.1 0.94 -1.6 0 0 0 -0.0053 0 0 0.13 -0.082 -0.76 0 0 5.5e+03 0.00074 1e+04 1 ++ 4 -0.98 1.1 0.94 -1.6 0 0 0 -0.0053 0 0 0.13 -0.082 -0.76 0 0 5.5e+03 2e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_000127 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 lambda_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -1 0.26 0.015 -0.7 -0.83 1 -0.4 -0.16 -0.087 5.4e+03 0.043 10 1.1 ++ 1 -1.4 0.9 0.74 -1.1 -1.3 0.3 -0.34 -0.016 -0.48 5.3e+03 0.011 1e+02 0.98 ++ 2 -1.6 1.1 0.94 -1.1 -1.1 0.52 -0.28 -0.028 -0.55 5.3e+03 0.0015 1e+03 1.1 ++ 3 -1.6 1.2 0.97 -1.1 -1.1 0.6 -0.27 -0.028 -0.54 5.3e+03 0.00012 1e+04 1 ++ 4 -1.6 1.2 0.97 -1.1 -1.1 0.6 -0.27 -0.028 -0.54 5.3e+03 3.6e-07 1e+04 1 ++ Considering neighbor 1/20 for current solution Considering neighbor 2/20 for current solution Attempt 44/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_000128 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 asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.42 -0.63 0.19 -0.0097 -1 -0.85 -0.26 -0.087 -0.19 -0.032 5.3e+03 0.036 10 1 ++ 1 -0.21 -1.1 0.73 0.35 -1.6 -1 -0.28 0.24 0.062 -0.14 5.1e+03 0.0098 1e+02 1.1 ++ 2 -0.36 -1.2 0.94 0.54 -1.7 -1 -0.28 0.25 0.053 -0.18 5.1e+03 0.00064 1e+03 1.1 ++ 3 -0.38 -1.2 0.96 0.56 -1.7 -1 -0.28 0.25 0.053 -0.18 5.1e+03 6.5e-06 1e+04 1 ++ 4 -0.38 -1.2 0.96 0.56 -1.7 -1 -0.28 0.25 0.053 -0.18 5.1e+03 8.2e-10 1e+04 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 45/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_000129 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 beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost lambda_cost b_headway beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_ma beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.57 -0.94 0 0 0 -0.84 1.3 -0.0031 0 0 -1 -0.046 0 0 5.6e+03 2.6 10 1 ++ 1 -0.57 -0.94 0 0 0 -0.84 1.3 -0.0031 0 0 -1 -0.046 0 0 5.6e+03 2.6 2.1 -2.1e+02 - 2 -0.57 -0.94 0 0 0 -0.84 1.3 -0.0031 0 0 -1 -0.046 0 0 5.6e+03 2.6 1 -2.6 - 3 -0.39 -1.5 0 0 0 -1.3 0.24 -0.0064 0 0 -1.3 0.078 0 0 5.5e+03 0.58 10 1 ++ 4 -0.51 -1.4 0 0 0 -1.1 0.19 -0.0059 0 0 -1.2 0.22 0 0 5.5e+03 0.022 1e+02 0.97 ++ 5 -0.52 -1.3 0 0 0 -1.1 0.19 -0.0059 0 0 -1.2 0.21 0 0 5.5e+03 5.2e-05 1e+03 1 ++ 6 -0.52 -1.3 0 0 0 -1.1 0.19 -0.0059 0 0 -1.2 0.21 0 0 5.5e+03 1.4e-09 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 22 unknown parameters [max: 50] *** Estimate b21_multiple_models_000130 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 5.9e+03 0.041 10 1 ++ 1 5.5e+03 0.053 1e+02 0.97 ++ 2 5.5e+03 0.0043 1e+03 1 ++ 3 5.5e+03 0.00016 1e+04 1 ++ 4 5.5e+03 2.1e-07 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_000131 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_tt b_cost lambda_cost b_headway asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -0.66 0.026 -0.0058 0.55 -1 1.7 -0.8 1 -0.0024 -0.36 -0.19 -0.042 -0.24 5.5e+03 1.9 1 0.77 + 1 -1 0.46 0.027 1.5 -1.3 0.99 -0.97 0.83 -0.008 -0.51 -0.16 -0.1 -0.65 5.1e+03 0.61 10 1.2 ++ 2 -0.98 0.66 0.38 1.9 -2.1 0.08 -1.7 -0.48 -0.0063 -0.12 0.065 -0.42 -1.8 5e+03 0.06 10 0.48 + 3 -1.4 0.7 0.42 2 -1.5 0.18 -1.5 -0.28 -0.0061 -0.33 0.065 -0.52 -1.9 4.9e+03 0.043 1e+02 1.1 ++ 4 -1.4 0.7 0.44 2 -1.6 0.26 -1.5 -0.02 -0.0062 -0.33 0.067 -0.46 -1.9 4.9e+03 0.0032 1e+03 1.1 ++ 5 -1.4 0.7 0.44 2 -1.6 0.28 -1.5 0.037 -0.0062 -0.31 0.062 -0.45 -1.8 4.9e+03 0.00067 1e+04 1 ++ 6 -1.4 0.7 0.44 2 -1.6 0.28 -1.5 0.045 -0.0062 -0.31 0.062 -0.45 -1.8 4.9e+03 6.4e-06 1e+05 1 ++ 7 -1.4 0.7 0.44 2 -1.6 0.28 -1.5 0.045 -0.0062 -0.31 0.062 -0.45 -1.8 4.9e+03 1.8e-07 1e+05 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b21_multiple_models_000132 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 5.8e+03 2.4 10 1 ++ 1 5.8e+03 2.4 1.5 -17 - 2 5.6e+03 0.85 1.5 0.71 + 3 5.5e+03 0.11 15 1.1 ++ 4 5.5e+03 0.0067 1.5e+02 1.1 ++ 5 5.5e+03 0.00029 1.5e+03 1 ++ 6 5.5e+03 2.8e-06 1.5e+03 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 18 unknown parameters [max: 50] *** Estimate b21_multiple_models_000133 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 5.7e+03 2.5 10 1 ++ 1 5.7e+03 2.5 3.3 -1.1e+04 - 2 5.7e+03 2.5 1.7 -13 - 3 5.3e+03 1.2 17 1.1 ++ 4 5.3e+03 1.2 1.2 -29 - 5 5.3e+03 1.2 0.62 -0.081 - 6 5.2e+03 0.011 6.2 0.98 ++ 7 5.2e+03 0.0076 62 0.96 ++ 8 5.2e+03 0.0018 6.2e+02 1.1 ++ 9 5.2e+03 1.2e-05 6.2e+03 1 ++ 10 5.2e+03 1.1e-09 6.2e+03 1 ++ Considering neighbor 4/20 for current solution Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_000134 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 beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_on asc_car_diff_se beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -1 -0.34 -0.026 0 0 0 -0.29 0 0 -0.35 -0.24 -0.019 0 0 5.9e+03 0.039 10 1.1 ++ 1 -2.1 0.81 0.76 0 0 0 -0.86 0 0 -0.88 0.18 0.015 0 0 5.6e+03 0.023 1e+02 1.1 ++ 2 -2.5 1.2 1.1 0 0 0 -0.95 0 0 -0.9 0.16 -0.097 0 0 5.5e+03 0.0038 1e+03 1.1 ++ 3 -2.5 1.2 1.2 0 0 0 -0.95 0 0 -0.9 0.16 -0.1 0 0 5.5e+03 0.00011 1e+04 1 ++ 4 -2.5 1.2 1.2 0 0 0 -0.95 0 0 -0.9 0.16 -0.1 0 0 5.5e+03 1e-07 1e+04 1 ++ Considering neighbor 5/20 for current solution Biogeme parameters read from biogeme.toml. Model with 18 unknown parameters [max: 50] *** Estimate b21_multiple_models_000135 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 5.8e+03 0.037 10 1 ++ 1 5.7e+03 0.0061 1e+02 1.1 ++ 2 5.7e+03 0.00019 1e+03 1 ++ 3 5.7e+03 1.9e-07 1e+03 1 ++ Considering neighbor 6/20 for current solution Considering neighbor 7/20 for current solution Attempt 46/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_000136 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 lambda_cost b_headway asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.53 0.2 -1 -0.23 1 -0.0043 -0.53 -0.13 5.5e+03 2.5 10 1 ++ 1 -0.53 0.2 -1 -0.23 1 -0.0043 -0.53 -0.13 5.5e+03 2.5 4.5 -3e+05 - 2 -0.53 0.2 -1 -0.23 1 -0.0043 -0.53 -0.13 5.5e+03 2.5 2.2 -1.1e+02 - 3 -0.53 0.2 -1 -0.23 1 -0.0043 -0.53 -0.13 5.5e+03 2.5 1.1 -3.7 - 4 -0.75 1.3 -1.6 -1.2 1.1 -0.0031 -0.22 -0.49 5.1e+03 0.22 11 1 ++ 5 -0.75 1.3 -1.6 -1.2 1.1 -0.0031 -0.22 -0.49 5.1e+03 0.22 1.1 -6.5 - 6 -0.73 2.4 -1.7 -1.4 0.48 -0.007 -0.27 -0.99 5e+03 0.27 11 1 ++ 7 -0.94 2.2 -1.6 -1.7 -0.12 -0.0061 -0.31 -1.8 4.9e+03 0.021 11 0.79 + 8 -0.93 2.2 -1.6 -1.5 -0.069 -0.0061 -0.28 -1.8 4.9e+03 0.00089 1.1e+02 1 ++ 9 -0.92 2.2 -1.6 -1.5 -0.038 -0.0061 -0.28 -1.9 4.9e+03 4.3e-05 1.1e+03 1 ++ 10 -0.92 2.2 -1.6 -1.5 -0.038 -0.0061 -0.28 -1.9 4.9e+03 3.9e-07 1.1e+03 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 47/100 Biogeme parameters read from biogeme.toml. Model with 5 unknown parameters [max: 50] *** Estimate b21_multiple_models_000137 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 b_headway asc_car Function Relgrad Radius Rho 0 -0.53 -1 -0.32 -0.0036 -0.47 5.6e+03 2.4 10 1 ++ 1 -0.47 -1.4 -1.1 -0.0051 -0.27 5.4e+03 0.095 1e+02 1 ++ 2 -0.38 -1.5 -1.1 -0.0054 -0.23 5.4e+03 0.013 1e+03 1 ++ 3 -0.38 -1.5 -1.1 -0.0054 -0.22 5.4e+03 0.0006 1e+04 1 ++ 4 -0.38 -1.5 -1.1 -0.0054 -0.22 5.4e+03 0.00016 1e+05 1 ++ 5 -0.38 -1.5 -1.1 -0.0054 -0.22 5.4e+03 4e-06 1e+05 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_000138 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 b_headway asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.53 0.16 -1 -0.28 -0.0046 -0.57 -0.12 5.5e+03 2.5 10 1 ++ 1 -0.72 2.3 -1.5 -0.97 -0.0052 -0.15 -0.25 5e+03 1.1 1e+02 0.94 ++ 2 -0.77 2.1 -1.7 -1.1 -0.006 -0.19 -0.25 5e+03 0.043 1e+03 1 ++ 3 -0.77 2.1 -1.7 -1.1 -0.0061 -0.19 -0.25 5e+03 0.00023 1e+04 1 ++ 4 -0.77 2.1 -1.7 -1.1 -0.0061 -0.19 -0.25 5e+03 2.1e-07 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_000139 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 beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost lambda_cost b_headway beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.91 0 0 0 -0.22 1 -0.0073 0 0 -1 0 0 5.9e+03 2.6 10 1 ++ 1 -0.91 0 0 0 -0.22 1 -0.0073 0 0 -1 0 0 5.9e+03 2.6 4.5 -2.8e+05 - 2 -0.91 0 0 0 -0.22 1 -0.0073 0 0 -1 0 0 5.9e+03 2.6 2.2 -1.6e+02 - 3 -0.91 0 0 0 -0.22 1 -0.0073 0 0 -1 0 0 5.9e+03 2.6 1.1 -7.3 - 4 -0.91 0 0 0 -0.22 1 -0.0073 0 0 -1 0 0 5.9e+03 2.6 0.56 -0.51 - 5 -1.2 0 0 0 -0.78 1 -0.0068 0 0 -0.85 0 0 5.7e+03 0.032 5.6 0.97 ++ 6 -1.2 0 0 0 -0.78 1 -0.0068 0 0 -0.85 0 0 5.7e+03 0.032 1 -8.7 - 7 -1.7 0 0 0 -1.4 -0.021 -0.0027 0 0 -0.99 0 0 5.7e+03 0.086 1 0.45 + 8 -1.4 0 0 0 -1.1 0.077 -0.0055 0 0 -0.98 0 0 5.6e+03 0.025 10 1 ++ 9 -1.4 0 0 0 -1.1 0.17 -0.0055 0 0 -0.99 0 0 5.6e+03 0.00033 1e+02 1 ++ 10 -1.4 0 0 0 -1.1 0.17 -0.0055 0 0 -0.99 0 0 5.6e+03 8.7e-07 1e+02 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 48/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_000140 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 asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.43 -0.73 0.84 -0.65 -1 -0.36 -0.1 -0.34 5.2e+03 0.041 10 1.1 ++ 1 -0.62 -0.95 1.8 -1 -2.5 -0.66 0.38 0.92 4.9e+03 0.012 1e+02 1.1 ++ 2 -0.63 -1.1 1.9 -1.1 -2.7 -0.7 0.43 1 4.9e+03 0.00079 1e+03 1 ++ 3 -0.63 -1.1 1.9 -1.1 -2.7 -0.7 0.43 1 4.9e+03 5.2e-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 b21_multiple_models_000141 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 asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.66 -0.78 0.62 -0.95 -1 -0.51 -0.26 -0.24 5.2e+03 0.034 10 1.1 ++ 1 -0.34 -0.96 1.8 -2.8 -1 -0.44 0.35 -0.43 4.9e+03 0.02 1e+02 1.1 ++ 2 -0.27 -1.1 1.9 -3.2 -1.1 -0.45 0.42 -0.45 4.9e+03 0.0013 1e+03 1 ++ 3 -0.27 -1.1 1.9 -3.2 -1.1 -0.45 0.42 -0.45 4.9e+03 7.3e-06 1e+04 1 ++ 4 -0.27 -1.1 1.9 -3.2 -1.1 -0.45 0.42 -0.45 4.9e+03 4.1e-10 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_000142 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 asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -1 -0.26 -0.026 0.23 -0.78 -0.41 -0.48 -0.34 -0.025 -0.15 5.6e+03 0.042 10 1 ++ 1 -1.2 0.36 0.18 2.1 -2.7 -0.96 -0.15 0.066 -0.17 -0.31 5e+03 0.032 1e+02 0.98 ++ 2 -1.5 0.64 0.46 1.8 -3.2 -1.1 -0.12 0.039 -0.29 -0.31 5e+03 0.0023 1e+03 1 ++ 3 -1.5 0.7 0.52 1.8 -3.2 -1.1 -0.11 0.037 -0.3 -0.29 5e+03 6.2e-05 1e+04 1 ++ 4 -1.5 0.7 0.52 1.8 -3.2 -1.1 -0.11 0.037 -0.3 -0.29 5e+03 5e-08 1e+04 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 49/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000143 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_tt b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.66 -1 2 0 0 0 0 0 -0.67 0 0 6.3e+03 0.14 1 0.42 + 1 -0.89 0 2.1 0 0 0 0 0 0.077 0 0 6.2e+03 0.29 1 0.19 + 2 -1.4 -0.053 3.1 0 0 0 0 0 -0.53 0 0 6e+03 0.52 1 0.43 + 3 -1.4 -0.053 3.1 0 0 0 0 0 -0.53 0 0 6e+03 0.52 0.5 -14 - 4 -1.4 -0.053 3.1 0 0 0 0 0 -0.53 0 0 6e+03 0.52 0.25 -6.5 - 5 -1.4 -0.053 3.1 0 0 0 0 0 -0.53 0 0 6e+03 0.52 0.12 -4.2 - 6 -1.4 -0.053 3.1 0 0 0 0 0 -0.53 0 0 6e+03 0.52 0.062 -1.6 - 7 -1.4 0.0095 3.1 0 0 0 0 0 -0.53 0 0 5.9e+03 1.1 0.062 0.5 + 8 -1.4 0.0095 3.1 0 0 0 0 0 -0.53 0 0 5.9e+03 1.1 0.031 -0.15 - 9 -1.5 -0.022 3.1 0 0 0 0 0 -0.54 0 0 5.9e+03 0.33 0.031 0.14 + 10 -1.5 -0.022 3.1 0 0 0 0 0 -0.54 0 0 5.9e+03 0.33 0.016 -0.32 - 11 -1.5 -0.0062 3 0 0 0 0 0 -0.56 0 0 5.9e+03 0.19 0.16 0.94 ++ 12 -1.5 -0.0062 3 0 0 0 0 0 -0.56 0 0 5.9e+03 0.19 0.078 -7.3 - 13 -1.5 -0.0062 3 0 0 0 0 0 -0.56 0 0 5.9e+03 0.19 0.039 -5.4 - 14 -1.5 -0.0062 3 0 0 0 0 0 -0.56 0 0 5.9e+03 0.19 0.02 -4.4 - 15 -1.5 -0.0062 3 0 0 0 0 0 -0.56 0 0 5.9e+03 0.19 0.0098 -3.8 - 16 -1.5 -0.0062 3 0 0 0 0 0 -0.56 0 0 5.9e+03 0.19 0.0049 -1.5 - 17 -1.5 -0.0013 3 0 0 0 0 0 -0.56 0 0 5.9e+03 0.0088 0.0049 0.86 + 18 -1.5 -0.0012 3 0 0 0 0 0 -0.56 0 0 5.9e+03 0.0032 0.049 1 ++ 19 -1.5 -0.0014 3 0 0 0 0 0 -0.58 0 0 5.9e+03 0.0027 0.49 1 ++ 20 -1.4 -0.0054 2.5 0 0 0 0 0 -0.54 0 0 5.9e+03 0.097 0.49 0.54 + 21 -1.5 -0.024 2 0 0 0 0 0 -0.57 0 0 5.8e+03 0.083 4.9 1.2 ++ 22 -1.2 -0.26 -0.73 0 0 0 0 0 -0.39 0 0 5.8e+03 0.038 4.9 0.65 + 23 -1.2 -0.26 -0.73 0 0 0 0 0 -0.39 0 0 5.8e+03 0.038 2.4 -2.5e+02 - 24 -1.2 -0.26 -0.73 0 0 0 0 0 -0.39 0 0 5.8e+03 0.038 1.2 -3.1 - 25 -0.48 -1.5 0.14 0 0 0 0 0 0.35 0 0 5.6e+03 0.032 12 1.3 ++ 26 -0.35 -1.6 0.53 0 0 0 0 0 0.24 0 0 5.6e+03 0.0079 12 0.84 + 27 -0.4 -1.6 0.46 0 0 0 0 0 0.2 0 0 5.5e+03 0.00061 1.2e+02 1.1 ++ 28 -0.41 -1.6 0.45 0 0 0 0 0 0.2 0 0 5.5e+03 6.9e-06 1.2e+03 1 ++ 29 -0.41 -1.6 0.45 0 0 0 0 0 0.2 0 0 5.5e+03 3.9e-10 1.2e+03 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 50/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_000144 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 beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.39 -0.76 1 -0.6 0 0 0 0 0 -0.37 -0.072 -0.43 0 0 5.4e+03 0.044 10 1.1 ++ 1 -0.37 -0.95 1.6 -1 0 0 0 0 0 -0.31 0.41 -1.3 0 0 5.2e+03 0.011 1e+02 1.1 ++ 2 -0.39 -1.1 1.7 -1.1 0 0 0 0 0 -0.32 0.42 -1.5 0 0 5.2e+03 0.00068 1e+03 1 ++ 3 -0.39 -1.1 1.7 -1.1 0 0 0 0 0 -0.32 0.42 -1.5 0 0 5.2e+03 4.2e-06 1e+03 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 51/100 Considering neighbor 0/20 for current solution Attempt 52/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_000145 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 b_headway asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.92 -0.039 -0.011 -1 -0.64 -0.0019 -0.46 -0.2 -0.047 5.6e+03 2.5 10 1 ++ 1 -0.89 0.82 0.5 -2.9 -2 -0.0045 -0.16 0.17 -0.14 5.2e+03 0.4 1e+02 1.1 ++ 2 -1.1 1.1 0.91 -3.2 -2.4 -0.0053 -0.18 0.17 -0.23 5.1e+03 0.075 1e+03 1.1 ++ 3 -1.1 1.2 0.95 -3.2 -2.4 -0.0055 -0.18 0.17 -0.23 5.1e+03 0.0012 1e+04 1 ++ 4 -1.1 1.2 0.95 -3.2 -2.4 -0.0055 -0.18 0.17 -0.22 5.1e+03 0.00012 1e+05 1 ++ 5 -1.1 1.2 0.95 -3.2 -2.4 -0.0055 -0.18 0.17 -0.22 5.1e+03 1e-07 1e+05 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 53/100 Considering neighbor 0/20 for current solution Attempt 54/100 Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_000146 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_tt b_cost asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.39 -0.63 -0.87 2 -0.81 -0.44 -0.21 5.9e+03 0.13 1 0.58 + 1 -0.41 -1.2 -0.47 1.8 -1.8 -0.43 0.18 5.3e+03 0.023 10 0.96 ++ 2 -0.41 -1.2 -0.47 1.8 -1.8 -0.43 0.18 5.3e+03 0.023 5 -2.4e+03 - 3 -0.41 -1.2 -0.47 1.8 -1.8 -0.43 0.18 5.3e+03 0.023 2.5 -15 - 4 -0.41 -1.2 -0.47 1.8 -1.8 -0.43 0.18 5.3e+03 0.023 1.2 -0.45 - 5 -0.34 -1.3 -1.1 0.52 -2.1 -0.49 0.27 5.2e+03 0.026 1.2 0.89 + 6 0.33 -1.2 -1.6 0.41 -2.3 -0.27 0.33 5.1e+03 0.0062 12 1 ++ 7 0.35 -1.3 -1.7 0.41 -2.4 -0.25 0.33 5.1e+03 7.8e-05 1.2e+02 1 ++ 8 0.35 -1.3 -1.7 0.41 -2.4 -0.25 0.33 5.1e+03 4.8e-08 1.2e+02 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 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 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_000147 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 beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost b_headway beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_wi beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.91 0.23 0 0 0 -0.42 -0.008 0 0 -1 -0.2 0 0 5.7e+03 2.5 10 1 ++ 1 -1.7 2.2 0 0 0 -0.97 -0.0062 0 0 -0.97 0.0081 0 0 5.3e+03 1.1 1e+02 1 ++ 2 -1.9 2.2 0 0 0 -1 -0.0064 0 0 -1 -0.049 0 0 5.3e+03 0.062 1e+03 1 ++ 3 -1.9 2.2 0 0 0 -1 -0.0064 0 0 -1 -0.042 0 0 5.3e+03 0.00046 1e+04 1 ++ 4 -1.9 2.2 0 0 0 -1 -0.0064 0 0 -1 -0.042 0 0 5.3e+03 2.6e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000148 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 beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost b_headway beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.91 0 0 0 -0.3 -0.0074 0 0 -1 0 0 5.9e+03 2.6 10 1 ++ 1 -1.4 0 0 0 -2 -0.0057 0 0 -0.78 0 0 5.6e+03 0.22 1e+02 0.99 ++ 2 -1.4 0 0 0 -2.2 -0.0055 0 0 -0.87 0 0 5.6e+03 0.0089 1e+03 1 ++ 3 -1.4 0 0 0 -2.2 -0.0055 0 0 -0.88 0 0 5.6e+03 1.2e-05 1e+04 1 ++ 4 -1.4 0 0 0 -2.2 -0.0055 0 0 -0.88 0 0 5.6e+03 4.4e-11 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000149 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 b_headway asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.42 -0.69 0.12 -0.0031 -1 -0.82 0.0011 -0.24 -0.033 -0.13 -0.034 5.3e+03 2.4 10 1.1 ++ 1 0.027 -1.2 0.73 0.33 -1.6 -1 -0.0044 -0.36 0.22 0.055 -0.15 5.1e+03 0.62 1e+02 1.1 ++ 2 -0.081 -1.2 0.94 0.52 -1.7 -1 -0.0058 -0.39 0.24 0.055 -0.18 5.1e+03 0.052 1e+03 1.1 ++ 3 -0.1 -1.2 0.97 0.55 -1.7 -1 -0.0059 -0.4 0.25 0.055 -0.18 5.1e+03 0.00056 1e+04 1 ++ 4 -0.1 -1.2 0.97 0.55 -1.7 -1 -0.0059 -0.4 0.25 0.055 -0.18 5.1e+03 2.6e-07 1e+04 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 58/100 Considering neighbor 0/20 for current solution Attempt 59/100 Considering neighbor 0/20 for current solution Attempt 60/100 Considering neighbor 0/20 for current solution Attempt 61/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_000150 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_tt b_cost beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.72 0.65 -0.95 2 0 0 0 -0.0015 0 0 -0.41 -0.3 0 0 6e+03 2.3 1 0.54 + 1 -0.93 1.6 -0.38 1.9 0 0 0 -0.0073 0 0 -0.15 -0.73 0 0 5.5e+03 0.17 1 0.86 + 2 -1.2 1.8 -0.83 0.89 0 0 0 -0.0047 0 0 -0.24 -0.85 0 0 5.3e+03 0.026 10 1 ++ 3 -0.51 1.8 -1.7 -0.05 0 0 0 -0.0059 0 0 0.19 -1.3 0 0 5.2e+03 0.12 10 0.49 + 4 -0.51 1.9 -1.7 0.32 0 0 0 -0.006 0 0 0.18 -1.4 0 0 5.2e+03 0.015 1e+02 1 ++ 5 -0.6 1.9 -1.6 0.34 0 0 0 -0.006 0 0 0.12 -1.3 0 0 5.2e+03 0.00078 1e+03 0.98 ++ 6 -0.6 1.9 -1.6 0.34 0 0 0 -0.006 0 0 0.12 -1.3 0 0 5.2e+03 8.4e-07 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000151 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 beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.65 -0.65 0 0 0 -0.0026 0 0 -0.4 0 0 5.7e+03 2.5 10 1.1 ++ 1 -0.41 -1.1 0 0 0 -0.0047 0 0 -0.064 0 0 5.6e+03 0.22 1e+02 1.1 ++ 2 -0.39 -1.1 0 0 0 -0.0052 0 0 -0.062 0 0 5.6e+03 0.0049 1e+03 1 ++ 3 -0.39 -1.1 0 0 0 -0.0052 0 0 -0.062 0 0 5.6e+03 2.4e-06 1e+03 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000152 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 6e+03 0.12 1 0.57 + 1 6e+03 0.12 0.5 -0.17 - 2 5.6e+03 0.022 5 0.91 ++ 3 5.6e+03 0.022 2.5 -12 - 4 5.6e+03 0.022 1.2 -0.22 - 5 5.4e+03 0.037 1.2 0.85 + 6 5.3e+03 0.0087 1.2 0.89 + 7 5.3e+03 0.00037 12 0.99 ++ 8 5.3e+03 2.9e-06 12 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_000153 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_tt b_cost beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.69 0.53 -1 1.8 0 0 0 0 0 -0.57 -0.28 0 0 6e+03 0.1 1 0.6 + 1 -1.1 1.5 -0.78 1.5 0 0 0 0 0 0.15 -0.67 0 0 5.4e+03 0.034 10 0.95 ++ 2 -1.1 1.5 -0.78 1.5 0 0 0 0 0 0.15 -0.67 0 0 5.4e+03 0.034 1.3 -3.9 - 3 -0.93 2.1 -1.8 0.15 0 0 0 0 0 0.33 -1.1 0 0 5.2e+03 0.017 1.3 0.82 + 4 -0.84 1.8 -1.6 0.31 0 0 0 0 0 0.25 -1.3 0 0 5.2e+03 0.0014 13 1 ++ 5 -0.87 1.8 -1.6 0.34 0 0 0 0 0 0.24 -1.4 0 0 5.2e+03 3.9e-05 1.3e+02 1 ++ 6 -0.87 1.8 -1.6 0.34 0 0 0 0 0 0.24 -1.4 0 0 5.2e+03 2.2e-08 1.3e+02 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000154 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 5.9e+03 2.6 10 1 ++ 1 5.8e+03 0.11 1e+02 1 ++ 2 5.8e+03 0.0017 1e+03 1 ++ 3 5.8e+03 1.9e-07 1e+03 1 ++ Considering neighbor 4/20 for current solution Considering neighbor 5/20 for current solution Attempt 62/100 Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_000155 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_tt b_cost b_headway asc_car Function Relgrad Radius Rho 0 -0.72 -1 2 -0.85 -0.00082 -0.46 5.9e+03 1.6 1 0.56 + 1 -1 0 2.1 -1.8 -0.0076 -0.84 5.8e+03 0.42 1 0.24 + 2 -1 0 2.1 -1.8 -0.0076 -0.84 5.8e+03 0.42 0.5 -0.05 - 3 -1.4 -0.039 2.3 -1.3 -0.0067 -1.1 5.6e+03 0.13 5 0.95 ++ 4 -1.4 -0.039 2.3 -1.3 -0.0067 -1.1 5.6e+03 0.13 2.5 -3.9 - 5 -1.4 -0.039 2.3 -1.3 -0.0067 -1.1 5.6e+03 0.13 1.2 -0.59 - 6 -1.4 -0.26 1 -0.7 -0.0003 -0.44 5.6e+03 0.31 1.2 0.38 + 7 -0.76 -0.82 1 -0.99 -0.0051 -0.46 5.4e+03 0.041 12 1.1 ++ 8 -0.25 -1.7 0.064 -1 -0.0054 -0.14 5.4e+03 0.068 12 0.53 + 9 -0.3 -1.6 0.37 -1 -0.0053 -0.18 5.4e+03 0.0066 1.2e+02 1 ++ 10 -0.37 -1.5 0.4 -1 -0.0053 -0.22 5.4e+03 0.00033 1.2e+03 1 ++ 11 -0.37 -1.5 0.4 -1 -0.0053 -0.22 5.4e+03 1.5e-06 1.2e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 5 unknown parameters [max: 50] *** Estimate b21_multiple_models_000156 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 b_headway asc_car Function Relgrad Radius Rho 0 -0.73 -0.67 -0.9 -0.0034 -0.57 5.4e+03 2.1 10 1.1 ++ 1 -0.49 -1.2 -1.1 -0.005 -0.29 5.3e+03 0.22 1e+02 1.1 ++ 2 -0.45 -1.3 -1.1 -0.0054 -0.26 5.3e+03 0.0055 1e+03 1 ++ 3 -0.45 -1.3 -1.1 -0.0054 -0.26 5.3e+03 0.0004 1e+04 1 ++ 4 -0.45 -1.3 -1.1 -0.0054 -0.26 5.3e+03 1e-05 1e+05 1 ++ 5 -0.45 -1.3 -1.1 -0.0054 -0.26 5.3e+03 7.1e-07 1e+05 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_000157 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_tt b_cost b_headway asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.67 0.5 -1 1.7 -0.91 -0.0026 -0.46 -0.23 5.5e+03 1.9 1 0.77 + 1 -0.94 1.5 -1.2 1 -1 -0.0053 -0.5 -0.36 5.1e+03 0.39 10 1.2 ++ 2 -0.32 2 -2.3 0.00089 -1.1 -0.0061 0.085 -0.36 5e+03 0.076 10 0.29 + 3 -0.73 2.1 -1.7 0.21 -1.1 -0.0061 -0.17 -0.34 5e+03 0.003 1e+02 1.1 ++ 4 -0.73 2.1 -1.7 0.38 -1.1 -0.0062 -0.18 -0.3 5e+03 0.0038 1e+03 0.99 ++ 5 -0.74 2.1 -1.7 0.39 -1.1 -0.0062 -0.19 -0.29 5e+03 1.1e-05 1e+04 1 ++ 6 -0.74 2.1 -1.7 0.39 -1.1 -0.0062 -0.19 -0.29 5e+03 2.9e-07 1e+04 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_000158 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_tt b_cost asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.73 0.39 -1 1.6 -0.73 -0.45 -0.21 5.5e+03 0.049 1 0.83 + 1 -1.1 1.4 -1.3 0.9 -1.1 -0.2 -0.35 5.1e+03 0.022 10 1.1 ++ 2 -0.87 2 -1.9 0.26 -1.1 0.037 -0.36 5e+03 0.012 10 0.82 + 3 -1 2 -1.7 0.36 -1.1 -0.061 -0.31 5e+03 0.0012 1e+02 1 ++ 4 -1 2 -1.7 0.38 -1.1 -0.064 -0.31 5e+03 3.1e-05 1e+03 1 ++ 5 -1 2 -1.7 0.38 -1.1 -0.064 -0.31 5e+03 3.6e-09 1e+03 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_000159 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_tt b_cost lambda_cost b_headway asc_car Function Relgrad Radius Rho 0 -0.68 -1 1.9 -0.84 1 -0.0011 -0.46 5.8e+03 1.7 1 0.67 + 1 -0.69 -1.8 0.85 -1.5 0.34 0.00068 -0.23 5.5e+03 0.27 10 0.92 ++ 2 -0.28 -1.5 0.63 -1.1 0.45 -0.006 -0.23 5.4e+03 0.05 1e+02 1 ++ 3 -0.29 -1.6 0.45 -1.1 0.61 -0.0054 -0.21 5.3e+03 0.0017 1e+03 0.93 ++ 4 -0.31 -1.6 0.46 -1.1 0.58 -0.0054 -0.22 5.3e+03 4.7e-05 1e+04 1 ++ 5 -0.31 -1.6 0.46 -1.1 0.58 -0.0054 -0.22 5.3e+03 5.3e-07 1e+04 1 ++ Considering neighbor 4/20 for current solution Considering neighbor 5/20 for current solution Attempt 63/100 Considering neighbor 0/20 for current solution Attempt 64/100 Considering neighbor 0/20 for current solution Attempt 65/100 Considering neighbor 0/20 for current solution Attempt 66/100 Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_000160 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 asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.52 -0.74 -1 -0.94 -0.46 -0.16 5.4e+03 0.044 10 1 ++ 1 0.21 -1.2 -2.9 -2.1 -0.24 0.26 5.1e+03 0.016 1e+02 1.1 ++ 2 0.31 -1.3 -3.3 -2.4 -0.27 0.33 5.1e+03 0.00089 1e+03 1 ++ 3 0.31 -1.3 -3.3 -2.4 -0.27 0.33 5.1e+03 2.8e-06 1e+03 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 67/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000161 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 lambda_cost asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -1 -0.24 -0.026 0.25 -0.81 -0.29 1 -0.52 -0.36 -0.027 -0.17 5.6e+03 0.05 10 1 ++ 1 -1 -0.24 -0.026 0.25 -0.81 -0.29 1 -0.52 -0.36 -0.027 -0.17 5.6e+03 0.05 4.5 -1.9e+05 - 2 -1 -0.24 -0.026 0.25 -0.81 -0.29 1 -0.52 -0.36 -0.027 -0.17 5.6e+03 0.05 2.2 -70 - 3 -1 -0.24 -0.026 0.25 -0.81 -0.29 1 -0.52 -0.36 -0.027 -0.17 5.6e+03 0.05 1.1 -1.9 - 4 -1.4 0.42 -0.0089 1.4 -1.6 -1.2 1 -0.34 -0.13 -0.083 -0.49 5.1e+03 0.041 11 0.99 ++ 5 -1.4 0.42 -0.0089 1.4 -1.6 -1.2 1 -0.34 -0.13 -0.083 -0.49 5.1e+03 0.041 0.95 -2.4 - 6 -1.7 0.68 0.098 2.1 -2.6 -1.4 0.42 -0.31 0.095 -0.17 -0.91 4.9e+03 0.015 9.5 1.1 ++ 7 -1.7 0.7 0.54 1.9 -2.9 -1.5 0.079 -0.25 0.079 -0.38 -1.7 4.9e+03 0.0042 95 1 ++ 8 -1.7 0.7 0.5 1.9 -2.9 -1.5 0.088 -0.23 0.077 -0.44 -1.8 4.9e+03 8e-05 9.5e+02 1 ++ 9 -1.7 0.7 0.5 1.9 -2.9 -1.5 0.088 -0.23 0.077 -0.44 -1.8 4.9e+03 3.5e-07 9.5e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 22 unknown parameters [max: 50] *** Estimate b21_multiple_models_000162 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 5.9e+03 0.041 10 1 ++ 1 5.5e+03 0.053 1e+02 0.97 ++ 2 5.5e+03 0.0043 1e+03 1 ++ 3 5.5e+03 0.00016 1e+04 1 ++ 4 5.5e+03 2.1e-07 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 19 unknown parameters [max: 50] *** Estimate b21_multiple_models_000163 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 5.8e+03 2.9 10 1 ++ 1 5.7e+03 0.32 1e+02 1.1 ++ 2 5.7e+03 0.014 1e+03 1 ++ 3 5.7e+03 2.1e-05 1e+04 1 ++ 4 5.7e+03 4.6e-11 1e+04 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000164 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 5.9e+03 0.04 10 1.1 ++ 1 5.9e+03 0.04 5 -1.1e+07 - 2 5.9e+03 0.04 2.5 -1.8e+02 - 3 5.9e+03 0.04 1.2 0.051 - 4 5.4e+03 0.043 12 1.1 ++ 5 5.4e+03 0.043 2.7 -3.1e+03 - 6 5.4e+03 0.043 1.4 -17 - 7 5.3e+03 0.057 1.4 0.48 + 8 5.2e+03 0.0044 14 0.91 ++ 9 5.2e+03 0.0019 14 0.89 + 10 5.2e+03 3.7e-05 1.4e+02 1 ++ 11 5.2e+03 5e-08 1.4e+02 1 ++ Considering neighbor 3/20 for current solution Considering neighbor 4/20 for current solution Attempt 68/100 Considering neighbor 0/20 for current solution Attempt 69/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_000165 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 asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -0.69 -0.13 -0.017 0.23 -1 -0.4 -0.33 -0.25 -0.02 -0.13 5.5e+03 0.051 10 1 ++ 1 -1.2 0.39 0.2 2.2 -1.6 -0.98 -0.074 0.017 -0.2 -0.21 5e+03 0.027 1e+02 0.96 ++ 2 -1.5 0.66 0.43 1.9 -1.7 -1.1 -0.076 0.0084 -0.3 -0.24 5e+03 0.0018 1e+03 1 ++ 3 -1.5 0.71 0.48 1.9 -1.7 -1.1 -0.072 0.0068 -0.3 -0.23 5e+03 4.3e-05 1e+04 1 ++ 4 -1.5 0.71 0.48 1.9 -1.7 -1.1 -0.072 0.0068 -0.3 -0.23 5e+03 2.4e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_000166 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 b_headway asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -1 0.41 0.027 -0.64 -0.9 -0.0035 -0.61 0.012 -0.09 5.4e+03 2.2 10 1.1 ++ 1 -1.1 0.93 0.76 -1.2 -1.1 -0.005 -0.36 0.1 -0.29 5.2e+03 0.36 1e+02 1.1 ++ 2 -1.3 1.1 0.95 -1.2 -1.1 -0.0055 -0.35 0.1 -0.28 5.2e+03 0.032 1e+03 1 ++ 3 -1.3 1.2 0.98 -1.2 -1.1 -0.0055 -0.35 0.11 -0.25 5.2e+03 0.00096 1e+04 1 ++ 4 -1.3 1.2 0.98 -1.2 -1.1 -0.0055 -0.35 0.11 -0.25 5.2e+03 3.7e-06 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_000167 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 asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.88 0.66 -0.79 -1 -0.36 -0.25 5.2e+03 0.047 10 1.1 ++ 1 -1.2 1.9 -1.1 -1.1 -0.28 -0.28 5.1e+03 0.014 1e+02 1.1 ++ 2 -1.3 2 -1.2 -1.1 -0.25 -0.3 5.1e+03 0.0007 1e+03 1 ++ 3 -1.3 2 -1.2 -1.1 -0.25 -0.3 5.1e+03 2.4e-06 1e+03 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_000168 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_tt b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.61 0.037 -0.014 -1 1.5 -0.44 -0.45 -0.34 -0.03 5.7e+03 0.08 1 0.84 + 1 -1.1 1 0.12 -1.8 0.54 -1.2 -0.022 0.043 -0.23 5.3e+03 0.012 10 0.95 ++ 2 -1.4 1.1 1.1 -1.5 0.43 -1.1 -0.081 -0.081 -0.67 5.3e+03 0.0015 1e+02 0.98 ++ 3 -1.4 1.1 0.95 -1.5 0.38 -1.1 -0.081 -0.077 -0.73 5.3e+03 8.8e-05 1e+03 1 ++ 4 -1.4 1.1 0.95 -1.5 0.38 -1.1 -0.081 -0.077 -0.73 5.3e+03 1.1e-07 1e+03 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_000169 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_tt b_cost b_headway asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.65 0.046 -0.0052 -0.98 1.8 -1 -0.0022 -0.35 -0.18 -0.042 5.6e+03 1.6 1 0.76 + 1 -0.98 1 0.075 -1.7 0.81 -1.1 -0.0048 -0.34 0.15 -0.11 5.2e+03 0.56 10 1 ++ 2 -1 1.1 1.1 -1.7 0.53 -1.1 -0.0055 -0.13 0.061 -0.41 5.2e+03 0.029 1e+02 0.99 ++ 3 -1.1 1.2 0.96 -1.6 0.5 -1.1 -0.0055 -0.18 0.071 -0.3 5.2e+03 0.0026 1e+03 1 ++ 4 -1.1 1.2 0.96 -1.6 0.5 -1.1 -0.0055 -0.18 0.071 -0.3 5.2e+03 5.5e-06 1e+03 1 ++ Considering neighbor 4/20 for current solution Considering neighbor 5/20 for current solution Attempt 70/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b21_multiple_models_000170 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_tt b_cost lambda_cost b_headway asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.55 -0.88 -0.9 1.8 -1 1 0.006 -0.27 -0.004 5.6e+03 2.2 1 0.78 + 1 0.45 -1.1 -1.1 1.3 -0.97 0.49 -0.0078 -0.68 0.34 5.3e+03 0.47 10 1.1 ++ 2 0.45 -1.1 -1.1 1.3 -0.97 0.49 -0.0078 -0.68 0.34 5.3e+03 0.47 1 -2.4 - 3 0.52 -1.1 -1.9 0.27 -1.3 0.69 -0.004 -0.54 0.46 5.2e+03 0.079 1 0.68 + 4 0.57 -1.3 -1.6 0.36 -1.1 0.62 -0.0058 -0.51 0.31 5.2e+03 0.015 10 0.99 ++ 5 0.56 -1.3 -1.6 0.39 -1.1 0.56 -0.0058 -0.53 0.32 5.2e+03 0.0001 1e+02 0.98 ++ 6 0.56 -1.3 -1.6 0.39 -1.1 0.56 -0.0058 -0.53 0.32 5.2e+03 1.3e-06 1e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000171 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 lambda_cost asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -0.68 -0.11 -0.016 0.24 -1 -0.29 1 -0.34 -0.26 -0.021 -0.14 5.5e+03 0.055 10 1 ++ 1 -0.68 -0.11 -0.016 0.24 -1 -0.29 1 -0.34 -0.26 -0.021 -0.14 5.5e+03 0.055 4.5 -2.2e+05 - 2 -0.68 -0.11 -0.016 0.24 -1 -0.29 1 -0.34 -0.26 -0.021 -0.14 5.5e+03 0.055 2.2 -88 - 3 -0.68 -0.11 -0.016 0.24 -1 -0.29 1 -0.34 -0.26 -0.021 -0.14 5.5e+03 0.055 1.1 -2.8 - 4 -1 0.49 0.0064 1.4 -1.6 -1.2 1 -0.036 -0.14 -0.077 -0.49 5.1e+03 0.018 11 1 ++ 5 -1 0.49 0.0064 1.4 -1.6 -1.2 1 -0.036 -0.14 -0.077 -0.49 5.1e+03 0.018 0.99 -4.4 - 6 -1.5 0.62 0.15 2.4 -1.7 -1.7 0.25 -0.099 -0.032 -0.22 -1.1 4.9e+03 0.013 9.9 1 ++ 7 -1.7 0.71 0.47 2 -1.6 -1.5 0.016 -0.19 0.046 -0.41 -1.8 4.9e+03 0.0019 99 1 ++ 8 -1.7 0.71 0.45 2 -1.6 -1.5 -0.035 -0.18 0.044 -0.45 -1.8 4.9e+03 9.4e-05 9.9e+02 1 ++ 9 -1.7 0.71 0.45 2 -1.6 -1.5 -0.035 -0.18 0.044 -0.45 -1.8 4.9e+03 9.2e-08 9.9e+02 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b21_multiple_models_000172 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 5.4e+03 0.045 10 1.1 ++ 1 5.3e+03 0.012 1e+02 1.1 ++ 2 5.3e+03 0.0009 1e+03 1 ++ 3 5.3e+03 7.2e-06 1e+04 1 ++ 4 5.3e+03 6.1e-10 1e+04 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 71/100 Biogeme parameters read from biogeme.toml. Model with 4 unknown parameters [max: 50] *** Estimate b21_multiple_models_000173 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 -0.71 -1 -0.28 -0.32 5.6e+03 0.042 10 1 ++ 1 -0.65 -1.5 -1 -0.1 5.4e+03 0.0059 1e+02 1 ++ 2 -0.63 -1.5 -1.1 -0.11 5.4e+03 9.8e-05 1e+03 1 ++ 3 -0.63 -1.5 -1.1 -0.11 5.4e+03 3.9e-08 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 5 unknown parameters [max: 50] *** Estimate b21_multiple_models_000174 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 b_headway asc_car Function Relgrad Radius Rho 0 -0.93 -1 -0.55 -0.0031 -0.75 5.6e+03 2.4 10 1 ++ 1 -0.42 -2.6 -1.1 -0.0064 -0.35 5.4e+03 0.15 1e+02 1 ++ 2 -0.39 -2.9 -1 -0.0054 -0.23 5.4e+03 0.014 1e+03 1 ++ 3 -0.39 -2.9 -1 -0.0054 -0.24 5.4e+03 0.0033 1e+04 1 ++ 4 -0.39 -2.9 -1 -0.0053 -0.23 5.4e+03 0.00019 1e+05 1 ++ 5 -0.39 -2.9 -1 -0.0053 -0.23 5.4e+03 7.9e-05 1e+06 1 ++ 6 -0.39 -2.9 -1 -0.0053 -0.23 5.4e+03 1.4e-05 1e+07 1 ++ 7 -0.39 -2.9 -1 -0.0053 -0.23 5.4e+03 1.4e-06 1e+07 1 ++ Considering neighbor 1/20 for current solution Considering neighbor 2/20 for current solution Attempt 72/100 Considering neighbor 0/20 for current solution Attempt 73/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_000175 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 asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -1 0.26 0.013 -0.7 -0.95 -0.37 -0.17 -0.092 5.4e+03 0.039 10 1.1 ++ 1 -1.5 0.89 0.71 -1 -1 -0.29 -0.032 -0.57 5.3e+03 0.0099 1e+02 1.1 ++ 2 -1.7 1.1 0.93 -1 -1.1 -0.28 -0.038 -0.65 5.3e+03 0.0011 1e+03 1.1 ++ 3 -1.7 1.2 0.96 -1 -1.1 -0.28 -0.038 -0.65 5.3e+03 1.3e-05 1e+04 1 ++ 4 -1.7 1.2 0.96 -1 -1.1 -0.28 -0.038 -0.65 5.3e+03 2e-09 1e+04 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 74/100 Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_000176 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 b_headway asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.37 -0.68 -1 -0.67 0.0024 -0.21 0.028 5.4e+03 2.7 10 1.1 ++ 1 0.56 -1.3 -1.6 -2 -0.0043 -0.26 0.26 5.1e+03 0.4 1e+02 1.1 ++ 2 0.66 -1.3 -1.7 -2.3 -0.0056 -0.32 0.28 5.1e+03 0.017 1e+03 1 ++ 3 0.66 -1.3 -1.7 -2.3 -0.0057 -0.32 0.28 5.1e+03 3e-05 1e+04 1 ++ 4 0.66 -1.3 -1.7 -2.3 -0.0057 -0.32 0.28 5.1e+03 1.5e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_000177 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_tt b_cost b_headway asc_car_ref asc_car_diff_ma Function Relgrad Radius Rho 0 -0.5 -0.77 -0.86 1.7 -1 0.0035 -0.28 -0.05 5.4e+03 2.1 1 0.87 + 1 0.27 -1.3 -1.6 0.68 -1.2 -0.0017 -0.54 0.39 5.1e+03 0.41 10 0.92 ++ 2 0.69 -1.3 -1.7 0.44 -1.1 -0.0059 -0.4 0.32 5.1e+03 0.022 1e+02 0.97 ++ 3 0.65 -1.3 -1.7 0.45 -1.1 -0.0058 -0.4 0.3 5.1e+03 2.5e-05 1e+03 1 ++ 4 0.65 -1.3 -1.7 0.45 -1.1 -0.0058 -0.4 0.3 5.1e+03 4.8e-07 1e+03 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000178 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 beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.52 -1 0 0 0 -0.0026 0 0 -0.34 0 0 5.7e+03 2.5 10 1 ++ 1 -0.18 -1.5 0 0 0 -0.0048 0 0 0.1 0 0 5.6e+03 0.13 1e+02 1 ++ 2 -0.17 -1.6 0 0 0 -0.0053 0 0 0.091 0 0 5.6e+03 0.0022 1e+03 1 ++ 3 -0.17 -1.6 0 0 0 -0.0053 0 0 0.091 0 0 5.6e+03 5e-07 1e+03 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 75/100 Considering neighbor 0/20 for current solution Attempt 76/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_000179 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 lambda_cost b_headway asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -0.53 -0.053 -0.0067 0.32 -1 -0.41 1 -0.004 -0.39 -0.22 -0.028 -0.15 5.4e+03 2.4 10 1 ++ 1 -0.53 -0.053 -0.0067 0.32 -1 -0.41 1 -0.004 -0.39 -0.22 -0.028 -0.15 5.4e+03 2.4 1.8 -24 - 2 -0.97 0.41 0.11 2.2 -1.6 -0.96 0.7 -0.004 -0.11 0.036 -0.15 -0.86 5e+03 1.1 18 1 ++ 3 -0.97 0.41 0.11 2.2 -1.6 -0.96 0.7 -0.004 -0.11 0.036 -0.15 -0.86 5e+03 1.1 1.1 -13 - 4 -1.2 0.68 0.16 2 -1.7 -1.7 -0.36 -0.0061 -0.26 -0.04 -0.25 -1.2 5e+03 0.13 1.1 0.26 + 5 -1.4 0.7 0.4 2.1 -1.6 -1.5 -0.24 -0.0061 -0.31 0.049 -0.45 -1.7 4.9e+03 0.0045 11 1.1 ++ 6 -1.4 0.71 0.42 2.1 -1.6 -1.5 -0.054 -0.0061 -0.32 0.048 -0.46 -1.8 4.9e+03 0.0019 1.1e+02 1.1 ++ 7 -1.4 0.71 0.42 2.1 -1.6 -1.5 -0.034 -0.0061 -0.31 0.045 -0.45 -1.8 4.9e+03 6.4e-05 1.1e+03 1 ++ 8 -1.4 0.71 0.42 2.1 -1.6 -1.5 -0.034 -0.0061 -0.31 0.045 -0.45 -1.8 4.9e+03 3.2e-07 1.1e+03 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 77/100 Biogeme parameters read from biogeme.toml. Model with 5 unknown parameters [max: 50] *** Estimate b21_multiple_models_000180 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_tt b_cost asc_car Function Relgrad Radius Rho 0 -0.68 -1 1.9 -0.64 -0.59 6e+03 0.11 1 0.59 + 1 -0.92 -0.75 1.6 -1.6 -0.024 5.4e+03 0.031 10 0.96 ++ 2 -0.92 -0.75 1.6 -1.6 -0.024 5.4e+03 0.031 1.2 -1.7 - 3 -0.68 -1.8 0.39 -2.3 0.03 5.3e+03 0.04 1.2 0.88 + 4 -0.48 -1.7 0.47 -2.3 0.054 5.2e+03 0.0029 12 0.95 ++ 5 -0.5 -1.7 0.48 -2.4 0.057 5.2e+03 2.1e-05 1.2e+02 1 ++ 6 -0.5 -1.7 0.48 -2.4 0.057 5.2e+03 1.2e-09 1.2e+02 1 ++ Considering neighbor 0/20 for current solution *** New pareto solution: asc:no_seg;train_cost_catalog:sqrt;train_headway_catalog:without_headway;train_tt_catalog:boxcox [10501.31230191711, np.float64(10535.41210642354), 5] Attempt 78/100 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 16 unknown parameters [max: 50] *** Estimate b21_multiple_models_000181 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 5.8e+03 3.1 1 0.67 + 1 5.3e+03 0.095 10 0.99 ++ 2 5.3e+03 0.095 5 -1.4e+03 - 3 5.3e+03 0.095 2.5 -13 - 4 5.3e+03 0.095 1.2 -0.49 - 5 5.2e+03 0.096 1.2 0.86 + 6 5.1e+03 0.015 1.2 0.87 + 7 5.1e+03 0.0033 12 0.95 ++ 8 5.1e+03 2.4e-05 1.2e+02 1 ++ 9 5.1e+03 3e-08 1.2e+02 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 81/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000182 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 beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.9 -1 0 0 0 -0.0019 0 0 -0.56 0 0 5.7e+03 2.6 10 1 ++ 1 -0.24 -2.8 0 0 0 -0.0046 0 0 0.076 0 0 5.5e+03 0.14 1e+02 1 ++ 2 -0.18 -3 0 0 0 -0.0052 0 0 0.083 0 0 5.5e+03 0.0033 1e+03 1 ++ 3 -0.18 -3 0 0 0 -0.0052 0 0 0.083 0 0 5.5e+03 1.9e-06 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 22 unknown parameters [max: 50] *** Estimate b21_multiple_models_000183 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 5.7e+03 0.039 10 1 ++ 1 5.6e+03 0.0083 1e+02 1.1 ++ 2 5.6e+03 0.00067 1e+03 1 ++ 3 5.6e+03 5.4e-06 1e+03 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_000184 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 beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -1 -1 0 0 0 0 0 -0.079 0 0 5.7e+03 0.036 10 1.1 ++ 1 -0.53 -2.7 0 0 0 0 0 0.14 0 0 5.6e+03 0.012 1e+02 1.1 ++ 2 -0.42 -3 0 0 0 0 0 0.19 0 0 5.6e+03 0.00049 1e+03 1 ++ 3 -0.42 -3 0 0 0 0 0 0.19 0 0 5.6e+03 6.5e-07 1e+03 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 82/100 Considering neighbor 0/20 for current solution Attempt 83/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b21_multiple_models_000185 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 beta_TRAIN_COST beta_TRAIN_COST beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_on asc_car_diff_se beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -1 0.066 -0.017 -1 0 0 0 0 0 -0.39 -0.27 -0.046 0 0 5.7e+03 0.041 10 1 ++ 1 -0.97 0.8 0.62 -2.8 0 0 0 0 0 0.19 -0.051 -0.68 0 0 5.5e+03 0.014 1e+02 1.1 ++ 2 -1.2 1.1 0.85 -3 0 0 0 0 0 0.22 -0.075 -0.76 0 0 5.5e+03 0.00099 1e+03 1.1 ++ 3 -1.2 1.1 0.88 -3 0 0 0 0 0 0.22 -0.076 -0.77 0 0 5.5e+03 1.6e-05 1e+04 1 ++ 4 -1.2 1.1 0.88 -3 0 0 0 0 0 0.22 -0.076 -0.77 0 0 5.5e+03 4.3e-09 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_000186 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 asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -1 -0.098 -0.023 -0.9 -0.46 -0.47 -0.33 -0.035 5.7e+03 0.05 10 1 ++ 1 -1.1 0.79 0.64 -2.9 -2.1 -0.076 0.2 -0.041 5.2e+03 0.02 1e+02 1 ++ 2 -1.3 1.1 0.91 -3.2 -2.4 -0.072 0.17 -0.21 5.2e+03 0.0017 1e+03 1.1 ++ 3 -1.4 1.1 0.95 -3.2 -2.4 -0.07 0.16 -0.23 5.2e+03 2.6e-05 1e+04 1 ++ 4 -1.4 1.1 0.95 -3.2 -2.4 -0.07 0.16 -0.23 5.2e+03 1e-08 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000187 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 5.7e+03 2.5 10 1 ++ 1 5.2e+03 0.86 1e+02 1 ++ 2 5.2e+03 0.085 1e+03 1.1 ++ 3 5.2e+03 0.002 1e+04 1 ++ 4 5.2e+03 1.4e-06 1e+04 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b21_multiple_models_000188 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 asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -1 -0.065 -1 -0.72 -0.048 -0.46 5.6e+03 0.042 10 1.1 ++ 1 -1.2 2.4 -2.5 -2.2 -0.17 0.87 5e+03 0.039 1e+02 0.94 ++ 2 -1.1 2.1 -3 -2.7 -0.16 1.1 5e+03 0.0016 1e+03 1 ++ 3 -1.1 2.1 -3.1 -2.8 -0.15 1.2 5e+03 1.6e-05 1e+04 1 ++ 4 -1.1 2.1 -3.1 -2.8 -0.15 1.2 5e+03 1.3e-09 1e+04 1 ++ Considering neighbor 3/20 for current solution Considering neighbor 4/20 for current solution Attempt 84/100 Biogeme parameters read from biogeme.toml. Model with 18 unknown parameters [max: 50] *** Estimate b21_multiple_models_000189 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 5.7e+03 2.5 10 1 ++ 1 5.7e+03 2.5 3.3 -1.1e+04 - 2 5.7e+03 2.5 1.7 -13 - 3 5.3e+03 1.2 17 1.1 ++ 4 5.3e+03 1.2 1.2 -29 - 5 5.3e+03 1.2 0.62 -0.081 - 6 5.2e+03 0.011 6.2 0.98 ++ 7 5.2e+03 0.0076 62 0.96 ++ 8 5.2e+03 0.0018 6.2e+02 1.1 ++ 9 5.2e+03 1.2e-05 6.2e+03 1 ++ 10 5.2e+03 1.1e-09 6.2e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_000190 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 beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_ma beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.81 -0.86 0 0 0 -0.97 0 0 -0.97 -0.0023 0 0 5.6e+03 0.036 10 1.1 ++ 1 -0.81 -1.3 0 0 0 -1.1 0 0 -1.1 0.23 0 0 5.5e+03 0.0062 1e+02 1.1 ++ 2 -0.81 -1.3 0 0 0 -1.1 0 0 -1.1 0.23 0 0 5.5e+03 0.0002 1e+03 1 ++ 3 -0.81 -1.3 0 0 0 -1.1 0 0 -1.1 0.23 0 0 5.5e+03 1.9e-07 1e+03 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b21_multiple_models_000191 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 5.8e+03 0.039 10 1.1 ++ 1 5.3e+03 0.058 1e+02 0.98 ++ 2 5.3e+03 0.0041 1e+03 1 ++ 3 5.3e+03 0.00015 1e+04 1 ++ 4 5.3e+03 1.7e-07 1e+04 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 85/100 Considering neighbor 0/20 for current solution Attempt 86/100 Considering neighbor 0/20 for current solution Attempt 87/100 Considering neighbor 0/20 for current solution Attempt 88/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_000192 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 beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost b_headway beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_ma beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -0.63 -0.89 0 0 0 -0.88 -0.0029 0 0 -0.94 -0.049 0 0 5.5e+03 2.6 10 1 ++ 1 -0.5 -1.3 0 0 0 -0.94 -0.0053 0 0 -1.1 0.15 0 0 5.5e+03 0.33 1e+02 1.1 ++ 2 -0.47 -1.4 0 0 0 -0.95 -0.0059 0 0 -1.1 0.14 0 0 5.5e+03 0.012 1e+03 1 ++ 3 -0.47 -1.4 0 0 0 -0.95 -0.0059 0 0 -1.1 0.14 0 0 5.5e+03 1.7e-05 1e+04 1 ++ 4 -0.47 -1.4 0 0 0 -0.95 -0.0059 0 0 -1.1 0.14 0 0 5.5e+03 3e-11 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b21_multiple_models_000193 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 asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.65 -0.8 0.72 -1 -0.95 -0.55 -0.27 -0.32 5.2e+03 0.045 10 1 ++ 1 -0.53 -0.93 1.9 -2.6 -1.4 -0.55 0.38 -1.5 4.9e+03 0.019 1e+02 1.1 ++ 2 -0.48 -1.1 2 -2.9 -1.5 -0.61 0.48 -2 4.8e+03 0.0013 1e+03 1.1 ++ 3 -0.47 -1.1 2 -3 -1.5 -0.62 0.49 -2 4.8e+03 9.5e-06 1e+04 1 ++ 4 -0.47 -1.1 2 -3 -1.5 -0.62 0.49 -2 4.8e+03 3.6e-09 1e+04 1 ++ Considering neighbor 1/20 for current solution Considering neighbor 2/20 for current solution Attempt 89/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b21_multiple_models_000194 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 beta_TRAIN_TT_S beta_TRAIN_TT_S b_cost beta_SM_TT_SCAL beta_SM_TT_SCAL asc_car_ref asc_car_diff_wi beta_CAR_TT_SCA beta_CAR_TT_SCA Function Relgrad Radius Rho 0 -1 0.15 0 0 0 -0.35 0 0 -0.045 -1 0 0 5.9e+03 0.076 10 1.1 ++ 1 -2.1 2.2 0 0 0 -1.2 0 0 -0.86 -1.1 0 0 5.2e+03 0.031 1e+02 1 ++ 2 -2.3 2.2 0 0 0 -1.5 0 0 -0.95 -1.5 0 0 5.2e+03 0.0012 1e+03 1 ++ 3 -2.3 2.2 0 0 0 -1.5 0 0 -0.95 -1.5 0 0 5.2e+03 3.9e-06 1e+03 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 90/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b21_multiple_models_000195 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 b_headway asc_car_ref asc_car_diff_on asc_car_diff_se asc_car_diff_wi Function Relgrad Radius Rho 0 -0.94 -0.088 -0.013 0.54 -1 -0.59 -0.0026 -0.5 -0.22 -0.044 -0.22 5.5e+03 2.6 10 1 ++ 1 -1.1 0.41 0.23 1.9 -2.6 -2.5 -0.0049 -0.31 0.083 -0.2 1 4.9e+03 0.75 1e+02 1 ++ 2 -1.3 0.66 0.45 1.9 -3 -2.8 -0.0061 -0.32 0.066 -0.34 1.2 4.9e+03 0.071 1e+03 1.1 ++ 3 -1.3 0.71 0.49 1.9 -3.1 -2.8 -0.0063 -0.32 0.064 -0.36 1.2 4.9e+03 0.0013 1e+04 1 ++ 4 -1.3 0.71 0.49 1.9 -3.1 -2.8 -0.0063 -0.32 0.064 -0.36 1.2 4.9e+03 4.5e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 91/100 Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000196 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 5.7e+03 2.5 10 1 ++ 1 5.2e+03 1 1e+02 1 ++ 2 5.2e+03 0.088 1e+03 1.1 ++ 3 5.2e+03 0.0024 1e+04 1 ++ 4 5.2e+03 2e-06 1e+04 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 92/100 Considering neighbor 0/20 for current solution Attempt 93/100 Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_000197 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 b_headway asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.86 1 -0.68 -0.91 -0.0036 -0.58 -0.25 5.2e+03 2.5 10 1.1 ++ 1 -0.95 1.9 -1.1 -1.1 -0.0054 -0.38 -0.32 5e+03 0.57 1e+02 1.1 ++ 2 -0.99 2 -1.2 -1.1 -0.0062 -0.38 -0.3 5e+03 0.034 1e+03 1 ++ 3 -1 2 -1.2 -1.1 -0.0063 -0.38 -0.28 5e+03 0.00011 1e+04 1 ++ 4 -1 2 -1.2 -1.1 -0.0063 -0.38 -0.28 5e+03 5.4e-06 1e+04 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 94/100 Considering neighbor 0/20 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 10 unknown parameters [max: 50] *** Estimate b21_multiple_models_000198 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 asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.41 -0.63 0.21 -0.0079 -1 -0.69 -0.26 -0.084 -0.21 -0.036 5.4e+03 0.038 10 1 ++ 1 -0.33 -1.1 0.73 0.32 -1.5 -1.1 -0.32 0.25 -0.071 -0.53 5.2e+03 0.0093 1e+02 1.1 ++ 2 -0.49 -1.2 0.93 0.51 -1.5 -1.1 -0.33 0.27 -0.081 -0.63 5.2e+03 0.00065 1e+03 1.1 ++ 3 -0.52 -1.2 0.96 0.53 -1.5 -1.1 -0.33 0.27 -0.082 -0.63 5.2e+03 6.9e-06 1e+04 1 ++ 4 -0.52 -1.2 0.96 0.53 -1.5 -1.1 -0.33 0.27 -0.082 -0.63 5.2e+03 9.2e-10 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_000199 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 beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.083 -0.77 -0.62 0 0 0 -0.0027 0 0 -0.47 0.023 0 0 5.6e+03 2.9 10 1.1 ++ 1 0.34 -1.1 -1.1 0 0 0 -0.005 0 0 -0.38 0.33 0 0 5.4e+03 0.37 1e+02 1.1 ++ 2 0.41 -1.2 -1.1 0 0 0 -0.0057 0 0 -0.39 0.32 0 0 5.4e+03 0.018 1e+03 1 ++ 3 0.41 -1.2 -1.1 0 0 0 -0.0057 0 0 -0.39 0.32 0 0 5.4e+03 3.6e-05 1e+04 1 ++ 4 0.41 -1.2 -1.1 0 0 0 -0.0057 0 0 -0.39 0.32 0 0 5.4e+03 1.4e-10 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 18 unknown parameters [max: 50] *** Estimate b21_multiple_models_000200 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 5.6e+03 2.7 10 1 ++ 1 5.6e+03 2.7 1.9 -91 - 2 5.6e+03 2.7 0.94 -1.1 - 3 5.4e+03 1.3 9.4 0.95 ++ 4 5.4e+03 0.081 94 1 ++ 5 5.4e+03 0.00075 9.4e+02 1 ++ 6 5.4e+03 1.1e-07 9.4e+02 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000201 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 5.5e+03 3 10 1.1 ++ 1 5.4e+03 0.45 1e+02 1.1 ++ 2 5.4e+03 0.039 1e+03 1.1 ++ 3 5.4e+03 0.00034 1e+04 1 ++ 4 5.4e+03 3.4e-08 1e+04 1 ++ Considering neighbor 3/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_000202 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 beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_wi beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.83 1 -0.71 0 0 0 -0.00098 0 0 -0.26 -0.43 0 0 5.4e+03 2.9 10 1.1 ++ 1 -0.83 1.7 -1.1 0 0 0 -0.0046 0 0 -0.054 -1.1 0 0 5.3e+03 0.58 1e+02 1.1 ++ 2 -0.85 1.8 -1.1 0 0 0 -0.006 0 0 -0.065 -1.3 0 0 5.3e+03 0.035 1e+03 1 ++ 3 -0.86 1.8 -1.1 0 0 0 -0.0061 0 0 -0.066 -1.3 0 0 5.3e+03 0.00014 1e+04 1 ++ 4 -0.86 1.8 -1.1 0 0 0 -0.0061 0 0 -0.066 -1.3 0 0 5.3e+03 2.2e-09 1e+04 1 ++ Considering neighbor 4/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b21_multiple_models_000203 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 b_headway asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.72 0.73 -0.83 -1 -0.0023 -0.37 -0.33 5.2e+03 2.3 10 1.1 ++ 1 -1.1 2 -0.98 -1.4 -0.0051 -0.48 -1.2 5e+03 0.77 1e+02 1.1 ++ 2 -1.2 2.1 -1 -1.4 -0.0061 -0.48 -1.8 5e+03 0.032 1e+03 1.1 ++ 3 -1.2 2.1 -1 -1.5 -0.0063 -0.49 -1.8 5e+03 5.4e-05 1e+04 1 ++ 4 -1.2 2.1 -1 -1.5 -0.0063 -0.49 -1.8 5e+03 3.8e-06 1e+04 1 ++ Considering neighbor 5/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000204 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 5.6e+03 3 10 1.1 ++ 1 5.3e+03 0.43 1e+02 1.1 ++ 2 5.3e+03 0.038 1e+03 1 ++ 3 5.3e+03 0.00034 1e+04 1 ++ 4 5.3e+03 3.1e-08 1e+04 1 ++ Considering neighbor 6/20 for current solution Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b21_multiple_models_000205 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 5.5e+03 2.7 10 1.1 ++ 1 5.4e+03 0.42 1e+02 1.1 ++ 2 5.4e+03 0.038 1e+03 1.1 ++ 3 5.4e+03 0.0004 1e+04 1 ++ 4 5.4e+03 5.3e-08 1e+04 1 ++ Considering neighbor 7/20 for current solution Considering neighbor 8/20 for current solution Attempt 98/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_000206 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 beta_TRAIN_COST beta_TRAIN_COST b_headway beta_SM_COST_SC beta_SM_COST_SC asc_car_ref asc_car_diff_ma beta_CAR_CO_SCA beta_CAR_CO_SCA Function Relgrad Radius Rho 0 -0.41 -0.74 -1 0 0 0 -0.00051 0 0 -0.44 -0.088 0 0 5.6e+03 2.8 10 1 ++ 1 0.54 -1.2 -2.8 0 0 0 -0.0045 0 0 -0.22 0.3 0 0 5.4e+03 0.37 1e+02 1.1 ++ 2 0.65 -1.2 -3 0 0 0 -0.0056 0 0 -0.23 0.32 0 0 5.4e+03 0.019 1e+03 1 ++ 3 0.65 -1.2 -3 0 0 0 -0.0057 0 0 -0.23 0.32 0 0 5.4e+03 4.8e-05 1e+04 1 ++ 4 0.65 -1.2 -3 0 0 0 -0.0057 0 0 -0.23 0.32 0 0 5.4e+03 2.5e-10 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 23 unknown parameters [max: 50] *** Estimate b21_multiple_models_000207 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 5.7e+03 3 10 1 ++ 1 5.6e+03 0.41 1e+02 1.1 ++ 2 5.6e+03 0.034 1e+03 1.1 ++ 3 5.6e+03 0.00026 1e+04 1 ++ 4 5.6e+03 2.1e-08 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 22 unknown parameters [max: 50] *** Estimate b21_multiple_models_000208 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 5.7e+03 0.039 10 1 ++ 1 5.6e+03 0.0083 1e+02 1.1 ++ 2 5.6e+03 0.00067 1e+03 1 ++ 3 5.6e+03 5.4e-06 1e+03 1 ++ Considering neighbor 2/20 for current solution Considering neighbor 3/20 for current solution Attempt 99/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b21_multiple_models_000209 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_tt b_cost lambda_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.55 -0.89 0.14 -0.0037 -0.93 1.8 -1 1 0.0058 -0.19 0.048 -0.13 -0.045 5.6e+03 2.2 1 0.82 + 1 -0.16 -1.2 1.1 0.11 -1.5 0.9 -1.1 0.62 -0.0057 -0.5 0.3 0.032 -0.18 5.2e+03 0.57 10 1 ++ 2 -0.019 -1.1 0.95 0.54 -1.9 0.35 -1.1 0.62 -0.0059 -0.37 0.31 -0.078 -0.52 5.1e+03 0.016 1e+02 0.93 ++ 3 -0.21 -1.1 0.96 0.51 -1.6 0.38 -1.1 0.53 -0.0059 -0.47 0.28 -0.057 -0.52 5.1e+03 0.00091 1e+03 0.97 ++ 4 -0.2 -1.1 0.96 0.51 -1.6 0.38 -1.1 0.54 -0.0059 -0.47 0.28 -0.059 -0.52 5.1e+03 1.1e-05 1e+04 1 ++ 5 -0.2 -1.1 0.96 0.51 -1.6 0.38 -1.1 0.54 -0.0059 -0.47 0.28 -0.059 -0.52 5.1e+03 4.7e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 23 unknown parameters [max: 50] *** Estimate b21_multiple_models_000210 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 5.7e+03 3 10 1 ++ 1 5.6e+03 0.41 1e+02 1.1 ++ 2 5.6e+03 0.034 1e+03 1.1 ++ 3 5.6e+03 0.00026 1e+04 1 ++ 4 5.6e+03 2.1e-08 1e+04 1 ++ Considering neighbor 1/20 for current solution Considering neighbor 2/20 for current solution Pareto file has been updated: b22_multiple_models.pareto Before the algorithm: 1 models, with 1 Pareto. After the algorithm: 175 models, with 7 Pareto. VNS algorithm completed. Postprocessing of the Pareto optimal solutions Pareto set initialized from file with 175 elements [7 Pareto] and 0 invalid elements. Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b22_multiple_models_000000.iter Cannot read file __b22_multiple_models_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. asc_train_ref asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -1 0.15 -1 -0.35 -0.045 -1 5.5e+03 0.043 10 1.1 ++ 1 -1.2 2.3 -2.4 -1.2 -0.18 -1.4 5e+03 0.026 1e+02 1 ++ 2 -1.2 2.1 -2.9 -1.4 -0.19 -1.9 4.9e+03 0.0017 1e+03 1 ++ 3 -1.2 2.1 -2.9 -1.5 -0.19 -1.9 4.9e+03 1.5e-05 1e+04 1 ++ 4 -1.2 2.1 -2.9 -1.5 -0.19 -1.9 4.9e+03 1.4e-09 1e+04 1 ++ Optimization algorithm has converged. Relative gradient: 1.3575712455194652e-09 Cause of termination: Relative gradient = 1.4e-09 <= 6.1e-06 Number of function evaluations: 16 Number of gradient evaluations: 11 Number of hessian evaluations: 5 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 5 Proportion of Hessian calculation: 5/5 = 100.0% Optimization time: 0:00:00.385619 Calculate second derivatives and BHHH File b22_multiple_models_000000.html has been generated. File b22_multiple_models_000000.yaml has been generated. Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b22_multiple_models_000001.iter Cannot read file __b22_multiple_models_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 b_cost b_headway asc_car_ref asc_car_diff_wi Function Relgrad Radius Rho 0 -0.53 0.21 -1 -0.24 -0.0043 -0.52 -0.14 5.5e+03 2.5 10 1 ++ 1 -0.88 2.4 -1.4 -1.3 -0.0052 -0.24 -1.3 5e+03 0.97 1e+02 0.96 ++ 2 -0.92 2.2 -1.6 -1.5 -0.006 -0.28 -1.8 4.9e+03 0.029 1e+03 1 ++ 3 -0.92 2.2 -1.6 -1.5 -0.0061 -0.28 -1.8 4.9e+03 0.00023 1e+04 1 ++ 4 -0.92 2.2 -1.6 -1.5 -0.0061 -0.28 -1.8 4.9e+03 5.6e-06 1e+04 1 ++ Optimization algorithm has converged. Relative gradient: 5.61836717542383e-06 Cause of termination: Relative gradient = 5.6e-06 <= 6.1e-06 Number of function evaluations: 16 Number of gradient evaluations: 11 Number of hessian evaluations: 5 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 5 Proportion of Hessian calculation: 5/5 = 100.0% Optimization time: 0:00:00.468167 Calculate second derivatives and BHHH File b22_multiple_models_000001.html has been generated. File b22_multiple_models_000001.yaml has been generated. Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b22_multiple_models_000002.iter Cannot read file __b22_multiple_models_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_ asc_train_diff_ b_time b_cost lambda_cost b_headway asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.47 -0.7 0.44 -1 -0.64 1 0.0022 -0.28 -0.067 -0.19 5.3e+03 2.7 10 1.1 ++ 1 -0.47 -0.7 0.44 -1 -0.64 1 0.0022 -0.28 -0.067 -0.19 5.3e+03 2.7 1.3 -3.2 - 2 -0.12 -1 1.7 -1.4 -1.2 0.84 -0.0024 -0.33 0.21 -0.62 4.9e+03 0.7 13 1 ++ 3 -0.12 -1 1.7 -1.4 -1.2 0.84 -0.0024 -0.33 0.21 -0.62 4.9e+03 0.7 0.64 0.017 - 4 0.019 -1.2 2.2 -1.6 -1.4 0.2 -0.0063 -0.52 0.31 -1.1 4.8e+03 0.15 6.4 1.1 ++ 5 -0.071 -1.2 2.2 -1.6 -1.5 -0.045 -0.0066 -0.68 0.45 -1.8 4.8e+03 0.03 64 1 ++ 6 -0.071 -1.2 2.2 -1.6 -1.5 -0.036 -0.0066 -0.69 0.46 -2 4.8e+03 0.0014 6.4e+02 1 ++ 7 -0.071 -1.2 2.2 -1.6 -1.5 -0.036 -0.0066 -0.69 0.46 -2 4.8e+03 4.6e-06 6.4e+02 1 ++ Optimization algorithm has converged. Relative gradient: 4.597929821476322e-06 Cause of termination: Relative gradient = 4.6e-06 <= 6.1e-06 Number of function evaluations: 21 Number of gradient evaluations: 13 Number of hessian evaluations: 6 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 8 Proportion of Hessian calculation: 6/6 = 100.0% Optimization time: 0:00:01.062942 Calculate second derivatives and BHHH File b22_multiple_models_000002.html has been generated. File b22_multiple_models_000002.yaml has been generated. Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b22_multiple_models_000003.iter Cannot read file __b22_multiple_models_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_ asc_train_diff_ b_time lambda_tt b_cost asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.45 -0.67 0.68 -0.95 2 -0.91 -0.5 -0.27 -0.33 5.8e+03 0.14 1 0.58 + 1 -0.78 -1.3 1.7 -0.38 1.8 -1.1 -0.53 0.15 -0.9 5.1e+03 0.028 10 0.95 ++ 2 -0.78 -1.3 1.7 -0.38 1.8 -1.1 -0.53 0.15 -0.9 5.1e+03 0.028 5 -2.5e+03 - 3 -0.78 -1.3 1.7 -0.38 1.8 -1.1 -0.53 0.15 -0.9 5.1e+03 0.028 2.5 -13 - 4 -0.78 -1.3 1.7 -0.38 1.8 -1.1 -0.53 0.15 -0.9 5.1e+03 0.028 1.2 0.071 - 5 -1.1 -1.3 2 -0.92 0.56 -1.5 -0.72 0.23 -1.2 4.9e+03 0.031 12 0.95 ++ 6 -0.34 -1.1 2.1 -1.7 -0.041 -1.5 -0.51 0.46 -1.8 4.8e+03 0.0035 12 0.82 + 7 -0.34 -1.1 2.1 -1.7 0.21 -1.5 -0.54 0.49 -2 4.8e+03 0.0038 1.2e+02 0.99 ++ 8 -0.39 -1.1 2.1 -1.6 0.22 -1.5 -0.56 0.48 -2 4.8e+03 4.7e-05 1.2e+03 0.99 ++ 9 -0.39 -1.1 2.1 -1.6 0.22 -1.5 -0.56 0.48 -2 4.8e+03 7.9e-09 1.2e+03 1 ++ Optimization algorithm has converged. Relative gradient: 7.901188754997834e-09 Cause of termination: Relative gradient = 7.9e-09 <= 6.1e-06 Number of function evaluations: 25 Number of gradient evaluations: 15 Number of hessian evaluations: 7 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 10 Proportion of Hessian calculation: 7/7 = 100.0% Optimization time: 0:00:01.073727 Calculate second derivatives and BHHH File b22_multiple_models_000003.html has been generated. File b22_multiple_models_000003.yaml has been generated. Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b22_multiple_models_000004.iter Cannot read file __b22_multiple_models_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 b_time b_cost asc_car Function Relgrad Radius Rho 0 -1 -1 -0.38 -0.11 5.6e+03 0.041 10 1.1 ++ 1 -0.65 -2.8 -0.89 -0.037 5.3e+03 0.016 1e+02 1.1 ++ 2 -0.49 -3.3 -1.1 -0.0039 5.3e+03 0.0015 1e+03 1.1 ++ 3 -0.48 -3.4 -1.1 -0.0026 5.3e+03 9.8e-06 1e+04 1 ++ 4 -0.48 -3.4 -1.1 -0.0026 5.3e+03 4.4e-10 1e+04 1 ++ Optimization algorithm has converged. Relative gradient: 4.432509937051248e-10 Cause of termination: Relative gradient = 4.4e-10 <= 6.1e-06 Number of function evaluations: 16 Number of gradient evaluations: 11 Number of hessian evaluations: 5 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 5 Proportion of Hessian calculation: 5/5 = 100.0% Optimization time: 0:00:00.310096 Calculate second derivatives and BHHH File b22_multiple_models_000004.html has been generated. File b22_multiple_models_000004.yaml has been generated. Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b22_multiple_models_000005.iter Cannot read file __b22_multiple_models_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_ref asc_train_diff_ asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_ma asc_car_diff_wi Function Relgrad Radius Rho 0 -0.42 -0.58 0.49 -1 -0.61 -0.36 -0.18 -0.22 5.3e+03 0.052 10 1 ++ 1 -0.4 -0.96 2.1 -1.5 -1.4 -0.47 0.37 -1.4 4.8e+03 0.021 1e+02 1 ++ 2 -0.37 -1.2 2.1 -1.6 -1.5 -0.55 0.45 -1.9 4.8e+03 0.0012 1e+03 1 ++ 3 -0.37 -1.2 2.1 -1.6 -1.5 -0.55 0.46 -2 4.8e+03 9.3e-06 1e+04 1 ++ 4 -0.37 -1.2 2.1 -1.6 -1.5 -0.55 0.46 -2 4.8e+03 3e-09 1e+04 1 ++ Optimization algorithm has converged. Relative gradient: 2.9723494479820364e-09 Cause of termination: Relative gradient = 3e-09 <= 6.1e-06 Number of function evaluations: 16 Number of gradient evaluations: 11 Number of hessian evaluations: 5 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 5 Proportion of Hessian calculation: 5/5 = 100.0% Optimization time: 0:00:00.450035 Calculate second derivatives and BHHH File b22_multiple_models_000005.html has been generated. File b22_multiple_models_000005.yaml has been generated. Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b22_multiple_models_000006.iter Cannot read file __b22_multiple_models_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 b_time lambda_tt b_cost asc_car Function Relgrad Radius Rho 0 -0.68 -1 1.9 -0.64 -0.59 6e+03 0.11 1 0.59 + 1 -0.92 -0.75 1.6 -1.6 -0.024 5.4e+03 0.031 10 0.96 ++ 2 -0.92 -0.75 1.6 -1.6 -0.024 5.4e+03 0.031 1.2 -1.7 - 3 -0.68 -1.8 0.39 -2.3 0.03 5.3e+03 0.04 1.2 0.88 + 4 -0.48 -1.7 0.47 -2.3 0.054 5.2e+03 0.0029 12 0.95 ++ 5 -0.5 -1.7 0.48 -2.4 0.057 5.2e+03 2.1e-05 1.2e+02 1 ++ 6 -0.5 -1.7 0.48 -2.4 0.057 5.2e+03 1.2e-09 1.2e+02 1 ++ Optimization algorithm has converged. Relative gradient: 1.2406510917479943e-09 Cause of termination: Relative gradient = 1.2e-09 <= 6.1e-06 Number of function evaluations: 20 Number of gradient evaluations: 13 Number of hessian evaluations: 6 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 7 Proportion of Hessian calculation: 6/6 = 100.0% Optimization time: 0:00:00.886563 Calculate second derivatives and BHHH File b22_multiple_models_000006.html has been generated. File b22_multiple_models_000006.yaml has been generated. Pareto: 7 Considered: 175 Removed: 7 .. GENERATED FROM PYTHON SOURCE LINES 62-67 .. code-block:: Python summary, description = compile_estimation_results( non_dominated_models, use_short_names=True ) print(summary) .. rst-class:: sphx-glr-script-out .. code-block:: none Model_000000 ... Model_000006 Number of estimated parameters 6 ... 5 Sample size 6768 ... 6768 Final log likelihood -4946.89 ... -5245.656 Akaike Information Criterion 9905.78 ... 10501.31 Bayesian Information Criterion 9946.7 ... 10535.41 asc_train_ref (t-test) -1.24 (-15) ... asc_train_diff_with_ga (t-test) 2.12 (24.2) ... b_time (t-test) -2.94 (-16.3) ... -1.67 (-21.5) b_cost (t-test) -1.47 (-17.8) ... -2.35 (-18.3) asc_car_ref (t-test) -0.19 (-3.16) ... asc_car_diff_with_ga (t-test) -1.9 (-9.51) ... b_headway (t-test) ... asc_train_diff_male (t-test) ... lambda_cost (t-test) ... asc_car_diff_male (t-test) ... lambda_tt (t-test) ... 0.476 (6.32) asc_train (t-test) ... -0.498 (-7.6) asc_car (t-test) ... 0.0566 (1.13) [18 rows x 7 columns] .. GENERATED FROM PYTHON SOURCE LINES 68-69 Explanation of the short names of the model. .. GENERATED FROM PYTHON SOURCE LINES 69-72 .. code-block:: Python for k, v in description.items(): if k != v: print(f'{k}: {v}') .. rst-class:: sphx-glr-script-out .. code-block:: none Model_000000: asc:GA;train_cost_catalog:log;train_headway_catalog:without_headway;train_tt_catalog:sqrt Model_000001: asc:GA;train_cost_catalog:log;train_headway_catalog:with_headway;train_tt_catalog:log Model_000002: asc:MALE-GA;train_cost_catalog:boxcox;train_headway_catalog:with_headway;train_tt_catalog:log Model_000003: asc:MALE-GA;train_cost_catalog:log;train_headway_catalog:without_headway;train_tt_catalog:boxcox Model_000004: asc:no_seg;train_cost_catalog:linear;train_headway_catalog:without_headway;train_tt_catalog:sqrt Model_000005: asc:MALE-GA;train_cost_catalog:log;train_headway_catalog:without_headway;train_tt_catalog:log Model_000006: asc:no_seg;train_cost_catalog:sqrt;train_headway_catalog:without_headway;train_tt_catalog:boxcox .. rst-class:: sphx-glr-timing **Total running time of the script:** (2 minutes 53.780 seconds) .. _sphx_glr_download_auto_examples_swissmetro_plot_b22a_multiple_models.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_b22a_multiple_models.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_b22a_multiple_models.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_b22a_multiple_models.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_