狮群优化算法基本程序原理
clear all
clc
SearchAgents_no=30; % 种群数量
Function_name='F2'; % F1 to F23 设定适应度函数
Max_iteration=50; % 设定最大迭代次数
% 获取适应度函数边界信息等
[lb,ub,dim,fobj]=Get_Functions_details(Function_name); %设定边界以及优化函数
[Best_score,Best_pos,LSO_curve]=LSO(SearchAgents_no,Max_iteration,lb,ub,dim,fobj); %开始优化
figure('Position',[269 240 660 290])
%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);
plot(LSO_curve,'Color','r','linewidth',1.5)
title('Objective space')
xlabel('Iteration');
ylabel('Best score obtained so far');
axis tight
grid on
box on
legend('LSO')
display(['The best solution obtained by LSO is : ', num2str(Best_pos)]);
display(['The best optimal value of the objective funciton found by LSO is : ', num2str(Best_score)]);
img =gcf; %获取当前画图的句柄
print(img, '-dpng', '-r600', './运行结果2.png') %即可得到对应格式和期望dpi的图像
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