基于MATLAB的头脑风暴优化算法

叁歲伎倆 2022-09-04 12:41 207阅读 0赞

% bso test  
clc  
clear all  
close all  
%funStr = 'rastrigin'; %output worksheet name  
%funName = @rastrigin; % fitness function name  
%n\_p = 500; % population size  
%n\_d = 2; % dimension  
%n\_c = 5; % number of clusters  
%rang\_l = -100; % left of dynamic range  
%rang\_r = 100; % right of dynamic range  
%max\_iteration = 50; % maximal number of iterations

warning off all

n\_p = 100; % population size  
n\_d = 30; % dimension  
n\_c = 5; % number of clusters

funStr = 'sphere30D5C'; %output worksheet name  
funName = @sphere; % fitness function name  
rang\_l = -100; % left of dynamic range sphere  
rang\_r = 100; % right of dynamic range

%funStr = 'rastrigin10D5C'; %output worksheet name  
%funName = @rastrigin; % fitness function name  
%rang\_l = -5.12; % left of dynamic range rastrigin  
%rang\_r = 5.12; % right of dynamic range

max\_iteration = 200; % maximal number of iterations

for idx = 1:50 % run times  
idx  
fit = bso2(funName,n\_p,n\_d,n\_c,rang\_l,rang\_r,max\_iteration); %run BSO one time  
% if idx <27  
% str = native2unicode(idx + 64);  
% else % assume idx <53  
% str =\['A',native2unicode(idx + 38)\];  
% end  
% xlswrite('bso2.xls',fit,funStr, \[str,'1'\]); % output best fitness over generation to EXCEL worksheet for each BSO run  
% \['run', num2str(idx)\]  
fit1=fit';  
fits(idx,1:max\_iteration)=fit1(1,1:max\_iteration);  
  
end  
fits=sum(fits)/idx;  
plot(fits,'-.');

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B-56

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