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

%Function description:

%minimize
%linearize = 1
%meanabs_pen(matrix_scenarios)
%Constraint: <= parameter_bound, linearize = 1
%polynom_abs(matrix_constraint_budget)
%Constraint: <= parameter_bound_1, linearize = 1
%cardn(parameter_alpha, matrix_constraint_card_new)
%Box: >= point_lowerbounds, <= point_upperbounds
%Solver: parameter_solver, precision = parameter_precision
%
%Input variables:
%
%Inputs                                    PSG Type    PSG Object                    Location in Problem Statement                                Class
%matrix_scenarios_benchmark                bench       matrix_scenarios              meanabs_pen(matrix_scenarios)                                double
%matrix_scenarios_data                     data        matrix_scenarios              meanabs_pen(matrix_scenarios)                                double
%matrix_scenarios_vars                     vars        matrix_scenarios              meanabs_pen(matrix_scenarios)                                cell
%matrix_constraint_budget_data             data        matrix_constraint_budget      polynom_abs(matrix_constraint_budget)                        double
%matrix_constraint_budget_vars             vars        matrix_constraint_budget      polynom_abs(matrix_constraint_budget)                        cell
%matrix_constraint_card_new_benchmark      bench       matrix_constraint_card_new    cardn(parameter_alpha, matrix_constraint_card_new)           double
%matrix_constraint_card_new_probability    prob        matrix_constraint_card_new    cardn(parameter_alpha, matrix_constraint_card_new)           double
%matrix_constraint_card_new_data           data        matrix_constraint_card_new    cardn(parameter_alpha, matrix_constraint_card_new)           double
%matrix_constraint_card_new_vars           vars        matrix_constraint_card_new    cardn(parameter_alpha, matrix_constraint_card_new)           cell
%point_lowerbounds_data                    data        point_lowerbounds             Box: >= point_lowerbounds, <= point_upperbounds              double
%point_lowerbounds_vars                    vars        point_lowerbounds             Box: >= point_lowerbounds, <= point_upperbounds              cell
%point_upperbounds_data                    data        point_upperbounds             Box: >= point_lowerbounds, <= point_upperbounds              double
%point_upperbounds_vars                    vars        point_upperbounds             Box: >= point_lowerbounds, <= point_upperbounds              cell
%parameter_bound_data                      data        parameter_bound               Constraint: <= parameter_bound, linearize = 1                double
%parameter_bound_1_data                    data        parameter_bound_1             Constraint: <= parameter_bound_1, linearize = 1              double
%parameter_alpha_data                      data        parameter_alpha               cardn(parameter_alpha, matrix_constraint_card_new)           double
%parameter_solver_data                     data        parameter_solver              Solver: parameter_solver, precision = parameter_precision    char
%parameter_precision_data                  data        parameter_precision           Solver: parameter_solver, precision = parameter_precision    char
%
%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_Stan\All\Optimal Hedging of CDO Book\data_problem_cdohedge_1_short\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_scenarios_benchmark,matrix_scenarios_data,matrix_scenarios_vars,matrix_constraint_budget_data,matrix_constraint_budget_vars,matrix_constraint_card_new_benchmark,matrix_constraint_card_new_probability,matrix_constraint_card_new_data,matrix_constraint_card_new_vars,point_lowerbounds_data,point_lowerbounds_vars,point_upperbounds_data,point_upperbounds_vars,parameter_bound_data,parameter_bound_1_data,parameter_alpha_data,parameter_solver_data,parameter_precision_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);