【优化求解】基于被囊群算法Tunicate Swarm Algorithm (TSA)求解单目标问题

1 简介

2 部分代码

clear all

clc

SearchAgents=30;

Fun_name='F2';

Max_iterations=1000;

[lowerbound,upperbound,dimension,fitness]=fun_info(Fun_name);

[Best_score,Best_pos,TSA_curve]=tsa(SearchAgents,Max_iterations,lowerbound,upperbound,dimension,fitness);

figure('Position',[500 500 660 290])

subplot(1,2,1);

func_plot(Fun_name);

title('Objective space')

xlabel('x_1');

ylabel('x_2');

zlabel([Fun_name,'( x_1 , x_2 )'])

subplot(1,2,2);

plots=semilogx(TSA_curve,'Color','g');

set(plots,'linewidth',2)

hold on

title('Objective space')

xlabel('Iterations');

ylabel('Best score');

axis tight

grid on

box on

legend('TSA')

img =gcf;  %获取当前画图的句柄

print(img, '-dpng', '-r600', './img2.png')         %即可得到对应格式和期望dpi的图像

display(['The best solution obtained by TSA is : ', num2str(Best_pos)]);

display(['The best optimal value of the objective funciton found by TSA is : ', num2str(Best_score)]);

3 仿真结果

4 参考文献

[1]屈迟文, 彭小宁. 信息共享的记忆被囊群算法[J]. 模式识别与人工智能.​