【优化求解】基于Levy改进哈里斯鹰算法LHHO求解最优目标matlab代码

1 简介

2 部分代码

% Leader Harris hawks optimization (LHHO) source Code Version 1.0

clearvars
close all
clc

disp('The LHHO is tracking the problem');

N=30; % Number of slime mould
Function_name='F23' % Name of the test function that can be from F1 to F23 
MaxIT=500; % Maximum number of iterations

[lb,ub,dim,fobj]=Get_Functions_details(Function_name); % Function details

Times=21; %Number of independent times you want to run the AOSMA
display(['Number of independent runs: ', num2str(Times)]);

for i=1:Times
[Rabbit_Energy(i),Rabbit_Location(i,:),CNVG(i,:)]=LHHO(N,MaxIT,lb,ub,dim,fobj);
display(['The optimal fitness of LHHO is: ', num2str(Rabbit_Energy(i))]);
end

[bestfitness,index]=min(Rabbit_Energy);
disp('--------Best Fitness, Average Fitness, Standard Deviation and Best Solution--------');
display(['The best fitness of LHHO is: ', num2str(bestfitness)]);
display(['The average fitness of LHHO is: ', num2str(mean(Rabbit_Energy))]);
display(['The standard deviation fitness of LHHO is: ', num2str(std(Rabbit_Energy))]);
display(['The best location of LHHO is: ', num2str(Rabbit_Location(index,:))]);

semilogy(CNVG(index,:),'LineWidth',3);
xlabel('Iterations');
ylabel('Best fitness obtained so far');
legend('LHHO');
box on;
axis tight;
grid off;

3 仿真结果

4 参考文献

[1]贾鹤鸣, 康立飞, 孙康健, 彭晓旭, 李瑶, & 姜子超. (2019). 哈里斯鹰算法优化脉冲耦合神经网络的图像自动分割. 应用科技(4).