%This Example for using users m-function problem_ksmavg_with_cvar_inequality_subroutine.m was created automatically by PSG Toolbox.

%Function description:

%problem_KSMavg_Cvar_inequality, minimize
%linearize = 1
%ksm_avg(matrix_xYi_norm_112, vector_Yi_norm, vector_qi)
%constraint: = 1
%linear(matrix_sYi_112)
%multiconstraint: >= vector_cvars_Y, linearize = 1
%pcvar(vector_alp,matrix_xYi_norm_112)
%box: >= 0, <= 1
%solver: car
%
%
%Input variables:
%
%Inputs                      PSG Type    PSG Object             Location in Problem Statement                              Class
%matrix_syi_112_data         data        matrix_syi_112         n/a                                                        double
%matrix_syi_112_vars         vars        matrix_syi_112         n/a                                                        cell
%matrix_xyi_norm_112_data    data        matrix_xyi_norm_112    n/a                                                        double
%matrix_xyi_norm_112_vars    vars        matrix_xyi_norm_112    n/a                                                        cell
%vector_qi_data              data        vector_qi              ksm_avg(matrix_xYi_norm_112, vector_Yi_norm, vector_qi)    double
%vector_alp_data             data        vector_alp             pcvar(vector_alp,matrix_xYi_norm_112)                      double
%vector_cvars_y_data         data        vector_cvars_y         n/a                                                        double
%vector_yi_norm_data         data        vector_yi_norm         n/a                                                        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_KSM\data_problem_KSMavg_with_Cvar_inequality\problem_ksmavg_with_cvar_inequality_subroutine_data.mat')

%Save variables from mat-file to Workspace:
tbpsg_export_to_workspace(toolboxstruc_arr)

%Run users m-function problem_ksmavg_with_cvar_inequality_subroutine:

[solution_str,outargstruc_arr] = problem_ksmavg_with_cvar_inequality_subroutine(matrix_syi_112_data,matrix_syi_112_vars,matrix_xyi_norm_112_data,matrix_xyi_norm_112_vars,vector_qi_data,vector_alp_data,vector_cvars_y_data,vector_yi_norm_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);

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