优化求解改进的萤火虫算法matlab源码

Posted 2021-06-16 MatlabQQ1575304183

一个简化的群搜索优化算法表示为大规模全局优化“SGSO”　提出了获得一个简单的算法性能优越在高维问题。SGSO采用一种改进的共享策略，使用一个简单的搜索方法搜索的角度。

function [fbestval,bestmember,Best] = SGSOforLS(fname,NDim,MaxIter)

% function [fbestval,bestmember,Best] = SGSOforLS(fname,NDim,MaxIter)
% Simplified Group Search Optimizer Algorithm for Large Scale Global Optimization
% Input Arguments: 
%   fname       - the name of the evaluation .m function
%   NDim        - dimension of the evalation function
%   MaxIter     - maximum iteration
% Example:  


PopSize=51;     % population of members

% Defined lower bound and upper bound.
Bound=eval(fname); 
LowerBound=zeros(NDim,1)+Bound(:,1);
UpperBound=zeros(NDim,1)+Bound(:,2);

basestep=0.5*(UpperBound-LowerBound); 

% Initialize swarm population
population=rand(NDim, PopSize).*(repmat(UpperBound-LowerBound,1,PopSize)) + repmat(LowerBound,1,PopSize);    

for iteration=1:MaxIter


    if (iteration)/5000==floor((iteration)/5000) 
        fprintf(1,'%e   ',fSequence(1));
        if (iteration)/25000==floor((iteration)/25000)
           fprintf(1,'\\n');
        end
    end
end

fbestval=fSequence(1);
% bestmember
% population
% fn=strcat(fname,'n',num2str(floor(rand(1)*1000)));
% dlmwrite(strcat(fn,'.txt'),Best);
plot(log10(Best))                    

​

完整代码添加QQ1575304183