objective_function_count = {objective_function_1: 0, objective_function_2: 0} # initial guesses initial_guess = [ 2.0, 2.0, 2.0, 5.0 ] # [in_vehicle=1, transfer_walk, origin_wait, transfer_wait, transfer_penalty] initial_cost_dict = sgs.runAssignmentCalculateErrorRMSN_all_error_terms( Visum=Visum, estimateList=initial_guess, obs_stops_df=observed_stop_df, obs_line_routes=observed_line_route_df) initial_cost = initial_cost_dict[objective_function_1] results_all_df = results_all_df.append( sgs.parse_error_from_dict_to_df(initial_cost_dict, initial_guess)) results_dict = {0: [initial_cost, initial_guess]} current_estimate = np.copy(initial_guess) best_rmsn = np.copy(initial_cost) np.random.seed(55) # measure time - start t_start = timeit.default_timer() for k in range(max_iterations):
objective_function_count = {objective_function_1: 0, objective_function_2: 0} # initial guesses initial_guess = [ 2.0, 2.0, 2.0, 5.0 ] # [in_vehicle=1, transfer_walk, origin_wait, transfer_wait, transfer_penalty] initial_cost_dict = sgs.runAssignmentCalculateErrorRMSN_all_error_terms( Visum=Visum, estimateList=initial_guess, obs_stops_df=observed_stop_df, obs_line_routes=observed_line_route_df) initial_cost = initial_cost_dict[objective_function_1] results_all_df = results_all_df.append( sgs.parse_error_from_dict_to_df(simulated_error_dict=initial_cost_dict, current_estimate=initial_guess, objective_function=objective_function_1)) results_dict = {0: [initial_cost, initial_guess]} current_estimate = np.copy(initial_guess) best_rmsn = np.copy(initial_cost) np.random.seed(55) # measure time - start t_start = timeit.default_timer() for k in range(max_iterations):
a = 4.833 A = 30 objective_function_1 = 'pax_trips_unlinked_rmsn' objective_function_2 = 'pass_trans_total_combined_rmsn' objective_function_count = {objective_function_1: 0, objective_function_2: 0} # initial guesses initial_guess = [1.0, 2.0, 2.0, 2.0, 5.0] # [in_vehicle, transfer_walk, origin_wait, transfer_wait, transfer_penalty] initial_cost_dict = sgs.runAssignmentCalculateErrorRMSN_all_error_terms(Visum=Visum, estimateList=initial_guess, obs_stops_df=observed_stop_df, obs_line_routes=observed_line_route_df) initial_cost = initial_cost_dict[objective_function_1] results_all_df = results_all_df.append(sgs.parse_error_from_dict_to_df(initial_cost_dict, initial_guess)) results_dict = {0: [initial_cost, initial_guess]} current_estimate = np.copy(initial_guess) best_estimate = np.copy(initial_guess) best_rmsn = np.copy(initial_cost) np.random.seed(55) # measure time - start t_start = timeit.default_timer() for k in range(max_iterations):