基于MATLAB实现的合作协同进化算法2维函数优化的源程序+使用说明文档.rar

function CoGA %COGA Summary of this function goes here % Detailed explanation goes here % 标准合作型协同进化遗传算法 clc; clear all; global POPSIZE POPULATION BESTINDIVIDUAL CURRENTBEST global P0 P1 P2 P3 T PC PM BINDEX WINDEX FAVER FMAX POPSIZE=20;T=3;Pc=0.95;Pm=0.3; t=1; bound=[-4 4]; PO1=initga(POPSIZE,bound); PO2=initga(POPSIZE,bound); %计算个体的适应度 [PO1,x2]=gafit(PO1,PO2,POPSIZE,1); [PO2,x1]=gafit(PO2,PO1,POPSIZE,1); %maitain the best individuals fitne1=PO1(:,2)';fitne2=PO2(:,2)'; fitne=[fitne1,fitne2]; fma1=max(fitne1);fma2=max(fitne2); in1=find(fma1==fitne1); in2=find(fma2==fitne2); best{t,1}=[PO1(in1(1),:),x2;PO2(in2(1),:),x1]; %search for the best fitness fmaa=[fma1,fma2];fma=max(fmaa); in=find(fma==fmaa); fmi1=min(fitne1);fmi2=min(fitne2); fav=mean(fitne); BINDEX1=findstr(fitne1,fma1); % the best fitness index of PO1 BINDEX2=findstr(fitne2,fma2); WINDEX1=findstr(fitne1,fmi1); % the worst fitness index of PO1 WINDEX2=findstr(fitne2,fmi2); % the worst fitness index of PO1 Bestin1=PO1(BINDEX1,:);Bestin2=PO2(BINDEX2,:); CURRENTBEST1{1,1}=Bestin1; CURRENTBEST2{1,1}=Bestin2; while t < T t=t+1; % generate the next time population %PO1 PO11=selectga(PO1,POPSIZE,1); PO12=crossga(PO11,POPSIZE,PC,1); PO13=uniformMutate(PO12,bound,PM); %PO2 PO21=selectga(PO2,POPSIZE,1); PO22=crossga(PO21,POPSIZE,PC,1); PO23=uniformMutate(PO22,bound,PM); %caculate the individual fitness [PO1,x2]=gafit(PO1,PO2,POPSIZE,1); [PO2,x1]=gafit(PO2,PO1,POPSIZE,1); %caculate the individual fitness [PO1,x2]=gafit(PO1,PO2,POPSIZE,1); [PO2,x1]=gafit(PO2,PO1,POPSIZE,1); fitne1=PO1(:,2)';fitne2=PO2(:,2)'; fitne=[fitne1,fitne2]; fma1=max(fitne1);fma2=max(fitne2); in1=find(fma1==fitne1); in2=find(fma2==fitne2); best{t,1}=[PO1(in1(1,1),:),x2(1,1);PO2(in2(1,1),:),x1(1,1)]; fmaa=[fma1,fma2];fma=max(fmaa); in=find(fma==fmaa); fmi1=min(fitne1);fmi2=min(fitne2); fav=mean(fitne); BINDEX1=findstr(fitne1,fma1); % the best fitness index of PO1 BINDEX2=findstr(fitne2,fma2); WINDEX1=findstr(fitne1,fmi1); % the worst fitness index of PO1 WINDEX2=findstr(fitne2,fmi2); % the worst fitness index of PO1 Bestin1=PO1(BINDEX1(1,1),:);Bestin2=PO2(BINDEX2(1,1),:); if Bestin1(:,2)>CURRENTBEST1{t-1,1}(:,2) CURRENTBEST1{t,1}=Bestin1; else PO1(WINDEX1(1,1),:)=CURRENTBEST1{t-1,1}; CURRENTBEST1{t,1}=CURRENTBEST1{t-1,1}; end if Bestin2(:,2)>CURRENTBEST2{t-1,1}(:,2) CURRENTBEST2{t,1}=Bestin2; else PO2(WINDEX2(1,1),:)=CURRENTBEST2{t-1,1}; CURRENTBEST2{t,1}=CURRENTBEST2{t-1,1}; end [PO13,x2]=gafit(PO13,PO23,POPSIZE,1); PO1=PO13; [PO23,x1]=gafit(PO23,PO13,POPSIZE,1); PO2=PO23; end best for i=1:T a(:,:,i)=best{i,1}; end a