投影寻踪 遗传算法MATLAB程序

投影寻踪遗传算法MATLAB程序投影寻踪遗传算法MATLAB程序投影寻踪遗传算法MATLAB程序xxx公司投影寻踪遗传算法MATLAB程序文件编号：文件日期：修订次数：第1.0次更改批准审核制定方案设计，管理制度clcclearcloseallAlpha=;X=load('d:\');fork=1:21eval(sprintf('symsa%d',k));enda=[a1,a2,a3,a4,a5,a6,a7,a8,a9,a10,a11,a12,a13,a14,a15,a16,a17,a18,a19,a20,a21];[n,p]=size(X);x=zeros(n,p);Xjmax=max(X);Xjmin=min(X);fori=1:nx(i,:)=(X(i,:)-Xjmin)./(Xjmax-Xjmin);end%构造投影指标fori=1:nZ(i)=sum(a.*x(i,:));end%计算投影指标函数meanZ=mean(Z);Sa=0;fork=1:nsa=(Z(i)-meanZ).^2;Sa=Sa+sa;Sa=sqrt(Sa/n);endR=Alpha*Sa;Da=0;fork=1:nrik=abs(Z(i)-Z(k));%ifR>rikDa=Da+rik;%endendQa=Sa*Da;%选择操作functionret=select(individuals,sizepop)=1./;sumfitness=sum;sumf=individuals./fitness;index=[];fori=1:sizepoppick=rand;whilepick==0pick=rand;endforj=1:sizepoppick=pick-sumf(j);ifpick<0index=[indexj];break;endendend=(index,:);=(index);ret=individuals;%交叉操作functionret=Cross(pcross,lenchrom,chrom,sizepop,bound)fori=1:sizepoppick=rand(1,2);whileprod(pick)==0pick=rand(1,2);endindex=ceil(pick.*sizepop);pick=rand;whilepick==0pick=rand;endifpick>pcrosscontinue;endflag=0;whileflag==0pick=rand;whilepick==0pick=rand;endpos=ceil(pick.*sum(lenchrom));pick=rand;v1=chrom(index(1),pos);v2=chrom(index(2),pos);chrom(index(1),pos)=pick*v2+(1-pick)*v1;chrom(index(2),pos)=pick*v1+(1-pick)*v2;flag1=test(lenchrom,bound,chrom(index(1),:),fcode);flag2=test(lenchrom,bound,chrom(index(2),:),fcode);ifflag1*flag2==0flag=0;elseflag=1;endendendret=chrom;%变异操作functionret=Mutation(pmutation,lenchrom,chrom,sizepoppop,bound)pick=rand;whilepick==0pick=rand;endindex=ceil(pick*sizepop);pick=rand;ifpick>pmutationcontinue;endflag=0;whileflag==0pick=rand;whilepick==0pick=rand;endpos=ceil(pick*sum(lenchrom));v=chrom(i,pos);v1=v-bound(pos,1);v2=bound(pos,2)-v;pick=rand;ifpick>delta=v2*(1-pick^((1-pop(1)/pop(2))^2));chrom(i,pos)=v+delta;elsedelta=v1*(1-pick^((1-pop(1)/pop(2))^2));chrom(i,pos)=v-delta;endflag=test(lenchrom,bound,chrom(1,:),fcode);endendendret=chrom;endend主函数clcclearmaxgen=200;sizepop=20;pcross=[];pmutation=[];lenchrom=[11111];bound=[0*pi;0*pi;0*pi;0*pi;0*pi;];individuals=struct('fitness',zeros(1,sizepop),'chrom',[]);avgfitness=[];bestfitness=[];bestchrom=[];fori=1:sizepop(1,:)=code(lenchrom,bound);x=(i,:);individuals,fitness(i)=fun(x);end[bestfitness,bestindex]=max;bestchrom=(bestindex,:);avgfitness=sum/sizepop;trace=[];fori=1:maxgenindividuals=Select(individuals,sizepop);avggitness=sum/sizepop;=Cross(pcross,lenchrom,,sizepop,bound);=Mutation(pmutation,lenchrom,,sizepop,[imaxgen],bound);ifmod(i,10)==0=nonlinear,sizepop);endforj=1:sizepopx=(j,:);(j)=fun(x);end[newbestfitness,newbestindex]=max;ifbes