main.m

% this script implements the hybrid of PSO and GWO optimization algorithm. 
%This code is developed at https://free-thesis.com
% GWO code from https://in.mathworks.com/matlabcentral/fileexchange/44974-grey-wolf-optimizer-gwo
%is extended to make it hybrid with PSO and better than GWO.

%%

clear all 
clc
close all

SearchAgents_no=30; % Number of search agents

Function_name='F18'; % Name of the test function that can be from F1 to F23 (Table 1,2,3 in the paper)

Max_iteration=500; % Maximum numbef of iterations

% Load details of the selected benchmark function
[lb,ub,dim,fobj]=Get_Functions_details(Function_name);

[Best_score,Best_pos,PSOGWO_cg_curve]=PSOGWO(SearchAgents_no,Max_iteration,lb,ub,dim,fobj);
[Alpha_score,Alpha_pos,GWO_cg_curve]=GWO(SearchAgents_no,Max_iteration,lb,ub,dim,fobj);

figure('Position',[500 500 660 290])
%Draw search space
subplot(1,2,1);
func_plot(Function_name);
title('Parameter space')
xlabel('x_1');
ylabel('x_2');
zlabel([Function_name,'( x_1 , x_2 )'])

%Draw objective space
subplot(1,2,2);
semilogy(PSOGWO_cg_curve,'Color','r')
hold on
semilogy(GWO_cg_curve,'Color','b')
title('Objective space')
xlabel('Iteration');
ylabel('Best score obtained so far');

axis tight
grid on
box on
legend('PSOGWO','GWO')

display(['The best solution obtained by PSOGWO is : ', num2str(Best_pos)]);
display(['The best optimal value of the objective funciton found by PSOGWO is : ', num2str(Best_score)]);
display(['The best solution obtained by GWO is : ', num2str(Alpha_pos)]);
display(['The best optimal value of the objective funciton found by GWO is : ', num2str(Alpha_score)]);