%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
%linear_sum_bool(matrix_bools)
%constraint: <=parameter_bound_2
%linearmulti_ubounds(pmatrix_upperbounds)
%constraint: >=parameter_bound_3
%linearmulti_lbounds(pmatrix_lowerbounds)
%box: types = point_bools
%solver: parameter_solver
%
%Input variables:
%
%Inputs                           PSG Type    PSG Object                  Location in Problem Statement                    Class
%matrix_bools_data                data        matrix_bools                linear_sum_bool(matrix_bools)                    double
%matrix_bools_vars                vars        matrix_bools                linear_sum_bool(matrix_bools)                    cell
%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
%pmatrix_lowerbounds_data         data        pmatrix_lowerbounds         linearmulti_lbounds(pmatrix_lowerbounds)         double
%pmatrix_lowerbounds_vars         vars        pmatrix_lowerbounds         linearmulti_lbounds(pmatrix_lowerbounds)         cell
%pmatrix_upperbounds_data         data        pmatrix_upperbounds         linearmulti_ubounds(pmatrix_upperbounds)         double
%pmatrix_upperbounds_vars         vars        pmatrix_upperbounds         linearmulti_ubounds(pmatrix_upperbounds)         cell
%point_bools_data                 data        point_bools                 box: types = point_bools                         double
%point_bools_vars                 vars        point_bools                 box: types = point_bools                         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                  double
%parameter_bound_2_data           data        parameter_bound_2           constraint: <=parameter_bound_2                  double
%parameter_bound_3_data           data        parameter_bound_3           constraint: >=parameter_bound_3                  double
%parameter_solver_data            data        parameter_solver            solver: parameter_solver                         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_1a_MIP\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_bools_data,matrix_bools_vars,matrix_scenarios_benchmark,matrix_scenarios_data,matrix_scenarios_vars,matrix_constraint_budget_data,matrix_constraint_budget_vars,pmatrix_lowerbounds_data,pmatrix_lowerbounds_vars,pmatrix_upperbounds_data,pmatrix_upperbounds_vars,point_bools_data,point_bools_vars,parameter_bound_data,parameter_bound_1_data,parameter_bound_2_data,parameter_bound_3_data,parameter_solver_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);