%This Example for using users m-function Optimization_subroutine.m was created automatically by PSG Toolbox. %Function description: %minimize %ksm_cvar_ni(0.0,matrix_mn,matrix_vr,vector_yi,vector_qi) %Constraint: = 1 %linear(matrix_ss) %MultiConstraint: >= vector_lb %wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) %Box: >= 0, <=1 % % %Input variables: % %Inputs PSG Type PSG Object Location in Problem Statement Class %matrix_mn data matrix_mn ksm_cvar_ni(0.0,matrix_mn,matrix_vr,vector_yi,vector_qi) double % matrix_mn_1 wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) % wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) %header_matrix_mn_vr vars matrix_mn ksm_cvar_ni(0.0,matrix_mn,matrix_vr,vector_yi,vector_qi) cell % matrix_vr wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) % matrix_mn_1 ksm_cvar_ni(0.0,matrix_mn,matrix_vr,vector_yi,vector_qi) % matrix_vr_1 wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) % wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) % wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) %matrix_vr data matrix_vr ksm_cvar_ni(0.0,matrix_mn,matrix_vr,vector_yi,vector_qi) double % matrix_vr_1 wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) % wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) %vector_yi_data data vector_yi ksm_cvar_ni(0.0,matrix_mn,matrix_vr,vector_yi,vector_qi) double %vector_qi_data data vector_qi ksm_cvar_ni(0.0,matrix_mn,matrix_vr,vector_yi,vector_qi) double %matrix_ss_data data matrix_ss linear(matrix_ss) double %matrix_ss_vars vars matrix_ss linear(matrix_ss) cell %matrix_ss_bench bench matrix_ss linear(matrix_ss) double %vector_param_data data vector_param wcvar_ni(vector_param, matrix_mn_1, matrix_vr_1) double %vector_lb_data data vector_lb MultiConstraint: >= vector_lb double % %Output variables: % %solution_str = string with solution of problem; %outargstruc_arr = array of output PSG data structures; %Load data from mat-file: load('D:\American Optimal Decisions\PSG\MATLAB\CS_Fitting_mixture_models_with_CVaR_constraints\case study\Matlab code\Optimization_subroutine_data.mat') %Save variables from mat-file to Workspace: tbpsg_export_to_workspace(toolboxstruc_arr) %Run users m-function Optimization_subroutine: [solution_str,outargstruc_arr] = Optimization_subroutine(matrix_mn,header_matrix_mn_vr,matrix_vr,vector_yi_data,vector_qi_data,matrix_ss_data,matrix_ss_vars,matrix_ss_bench,vector_param_data,vector_lb_data); %Extract Objective: val_obj = tbpsg_objective(solution_str, outargstruc_arr); disp(' '); disp('Objective = '); disp(val_obj); %Extract optimal solution: point_data = tbpsg_optimal_point_data(solution_str, outargstruc_arr); disp(' '); disp('Optimal point = '); disp(point_data); %Extract structure containing PSG solution reports: output_structure = tbpsg_solution_struct(solution_str, outargstruc_arr); disp(' '); disp('Structure with PSG solution = '); disp(output_structure); %Uncomment the following lines to extract solutions details: %output = tbpsg_isoptimal(solution_str, outargstruc_arr); %output = tbpsg_function_data(solution_str, outargstruc_arr); %output = tbpsg_function_names(solution_str, outargstruc_arr); %output = tbpsg_time(solution_str, outargstruc_arr); %output = tbpsg_optimal_point_vars(solution_str, outargstruc_arr); %output = tbpsg_constraints_vars(solution_str, outargstruc_arr); %output = tbpsg_slack_data(solution_str, outargstruc_arr); %output = tbpsg_dual_data(solution_str, outargstruc_arr); %output = tbpsg_vector_constraint_data(solution_str, outargstruc_arr); %output = tbpsg_vector_dual_data(solution_str, outargstruc_arr); %output = tbpsg_vector_slack_data(solution_str, outargstruc_arr); %output = tbpsg_matrix_data(solution_str, outargstruc_arr); %output = tbpsg_matrix_vars(solution_str, outargstruc_arr); %output = tbpsg_vector_data(solution_str, outargstruc_arr); %=======================================================================| %American Optimal Decisions, Inc. Copyright | %Copyright ©American Optimal Decisions, Inc. 2007-2017. | %American Optimal Decisions (AOD) retains copyrights to this material. | % | %Permission to reproduce this document and to prepare derivative works | %from this document for internal use is granted, provided the copyright | %and “No Warranty” statements are included with all reproductions | %and derivative works. | % | %For information regarding external or commercial use of copyrighted | %materials owned by AOD, contact AOD at support@aorda.com. | %=======================================================================|