% This program implements  the Case Study
% CS_Project_Selection_FXCHG with riskconstrparam 


%Solving Problem 1 (linear)
clear;

% load data
load('CS_Project_Selection_FXCHG_riskconstrprog_data.mat');

% specifies a set of values of parameter (upper bound on init capital) for which
% runs should be conducted
UB_Init_Capital = [300 350 400 500 600 650];

% set solver options
options.Linearization = 'On';
options.Solver = 'CAR';
options.Precision = 6;
options.Stages = 6;

% set variables type option (boolean)
options.Types = 1;

% optimize portfolio for specified  values of the parameter,
% and build efficient frontier
[Objectives, UB_Init_Capital, Points, GraphHandle2]=riskconstrparam ([],'linear', [], [], [], [], ...
    0.0000001, matrix_costs, [], [], matrix_NPV,  UB_Init_Capital(1), [], [], [], [], point_lowerbounds, point_upperbounds, 'r', [],[],[],...
    [], [], UB_Init_Capital, [], options);
   
%Create plots for output
subplot(2,1,1);
  plot2 = plot(UB_Init_Capital, Objectives, '-ob', 'LineWidth', 1.5, 'MarkerFaceColor', 'b', 'MarkerSize', 3);
            title('Objective vs Parameter: linear', 'FontSize', 12);
            xlabel('Parameter');
            ylabel('Objective');
            grid on;

% Display solution
fprintf('\n%12s','Table 1: Solution of Problem 1 (linear)');
Points = Points';
            
fprintf('\n%12s','UB_Init_Capital');
for i=1:1:length(UB_Init_Capital)
fprintf('%12.0f', UB_Init_Capital(i));
end

fprintf('\n%5s','Objective        ');
for i=1:1:length(UB_Init_Capital)
    fprintf('%12.4f', Objectives(i));
end
fprintf('\n%5s','Optimal points');
fprintf('\n%5s','Project');
for j=1:length(Points(:,1))
    fprintf('\n%8s', strcat('Project', num2str(j)));
    fprintf('        ');
   for i=1:1:length(UB_Init_Capital)
    fprintf('%12f', Points(j,i));
   end
end 
fprintf('\n');


%--------------------------------------------------------------------------
%Solving Problem 2 (fxchg_pos)
%Clear problem statement and iargstruc_arr
clear;
% load data
load('CS_Project_Selection_FXCHG_riskconstrprog_data.mat');

%global psg_suppress_warning;
mpsg_suppress_message = 'Off';

% specifies a set of values of parameter (upper bound on init capital) for which
% runs should be conducted
UB_Init_Capital = [300 350 400 500 600 650];

clear options;

% set solver options
options.Linearization = 'On';
options.Solver = 'CAR';
options.Precision = 6;
options.Stages = 6;
options.Warnings = 'Off';

% optimize portfolio for specified  values of the parameter,
% and build efficient frontier
[Objectives, UB_Init_Capital, Points, GraphHandle]=riskconstrparam ([],'fxchg_pos', [], [], [], [], ...
    0.0000001, matrix_costs, [], [], matrix_NPV,  UB_Init_Capital(1), [], [], [], [], point_lowerbounds, point_upperbounds, 'r', [],[],[],...
    [], [], UB_Init_Capital, [], options);

%Create plots for output
subplot(2,1,2);
            plot1 = plot(UB_Init_Capital, Objectives, '-ob', 'LineWidth', 1.5, 'MarkerFaceColor', 'b', 'MarkerSize', 3);
            title('Objective vs Parameter: fxchg\_pos', 'FontSize', 12);
            xlabel('Parameter');
            ylabel('Objective');
            grid on;

% Display solution
fprintf('\n%12s','Table 2: Solution of Problem 2 (fxchg_pos)');
Points = Points';

fprintf('\n%12s','UB_Init_Capital');
for i=1:1:length(UB_Init_Capital)
    fprintf('%12.0f', UB_Init_Capital(i));
end

fprintf('\n%5s','Objective        ');
for i=1:1:length(UB_Init_Capital)
    fprintf('%12.4f', Objectives(i));
end
fprintf('\n%5s','Optimal points');
fprintf('\n%5s','Project');
for j=1:length(Points(:,1))
    fprintf('\n%8s', strcat('Project', num2str(j)));
    fprintf('        ');
   for i=1:1:length(UB_Init_Capital)
    fprintf('%12f', Points(j,i));
   end
end 

disp('  ')

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