%=======================================================================
%To solve optimization problem:
%Download and unpack the following zipped file from 'Data':
%'Mat_data_problem_2_Korea_retail_bound_0_2_short.zip'
%Run program 'problem_2_Korea_retail_bound_0_2_short.m'
%=======================================================================

clc;
clear;

%Load data:
load('problem_2_Korea_retail_bound_0_2_short_data.mat')
%Define options for PSG solver:
stroptions.Stages = 10;
%Define input arguments:
string = 'var_dev';
w = 0.9984;

%Solve optimization problems:
[xout, fval, status, output] = riskprog(string, w, H, [], p, [], A, b, [], [], lb, ub, [], stroptions);
 
%Display results:
disp(' ');
disp('Results: ');
%Display status of optimization problem:
disp(sprintf('status of optimization problem = %s', status));
%Display solving time:
disp(sprintf('solving time = %g', output.solving_time));
%Display objective:
disp(sprintf('objective = %g', fval));
%Display function:
disp(sprintf('var_dev= %g', output.frval));
%Display left hand sides of linear inequality:
disp(sprintf('linear inequality = %g', output.fAval));
%Display residual of linear inequality:
disp(sprintf('residual of linear inequality = %g', output.rAval));
%Display optimal point:
disp('optimal point = ');
disp(xout');