遗传算法
function youhuafun D=code; N=50; % Tunable maxgen=50; % Tunable crossrate=0.5; %Tunable muterate=0.08; %Tunable generation=1; num = length(D); fatherrand=randint(num,N,3);score = zeros(maxgen,N); whilegeneration<=maxgen ind=randperm(N-2)+2; % 随机配对交叉 A=fatherrand(:,ind(1:(N-2)/2)); B=fatherrand(:,ind((N-2)/2+1:end)); % 多点交叉 rnd=rand(num,(N-2)/2); ind=rnd tmp=A(ind); A(ind)=B(ind); B(ind)=tmp; % % 两点交叉% for kk=1:(N-2)/2 % rndtmp=randint(1,1,num)+1; % tmp=A(1:rndtmp,kk); % A(1:rndtmp,kk)=B(1:rndtmp,kk); % B(1:rndtmp,kk)=tmp; % end fatherrand=; % 变异 rnd=rand(num,N); ind=rnd =size(ind); tmp=randint(m,n,2)+1; tmp(:,1:2)=0; fatherrand=tmp+fatherrand; fatherrand=mod(fatherrand,3); % fatherrand(ind)=tmp; %评价、选择 scoreN=scorefun(fatherrand,D);% 求得N个个体的评价函数 score(generation,:)=scoreN; =sort(scoreN); sumscore=cumsum(scoreSort); sumscore=sumscore./sumscore(end); childind(1:2)=scoreind(end-1:end); for k=3:N tmprnd=rand; tmpind=tmprnd difind=; if ~any(difind) difind(1)=1; end childind(k)=scoreind(logical(difind)); end fatherrand=fatherrand(:,childind); generation=generation+1; end % score maxV=max(score,[],2); minV=11*300-maxV; plot(minV,'*');title('各代的目标函数值'); F4=D(:,4); FF4=F4-fatherrand(:,1); FF4=max(FF4,1); D(:,5)=FF4; save DData D function D=code load youhua.mat % properties F2 and F3 F1=A(:,1); F2=A(:,2); F3=A(:,3); if(max(F2)>1450)||(min(F2)<=900) error('DATA property F2 exceed it''s range(900,1450]') end % get group property F1 ofdata, according to F2 value F4=zeros(size(F1)); for ite=11:-1:1 index=find(F2<=900+ite*50); F4(index)=ite; end D=; function ScoreN=scorefun(fatherrand,D)F3=D(:,3); F4=D(:,4); N=size(fatherrand,2); FF4=F4*ones(1,N); FF4rnd=FF4-fatherrand; FF4rnd=max(FF4rnd,1); ScoreN=ones(1,N)*300*11; % 这里有待优化for k=1:N FF4k=FF4rnd(:,k); for ite=1:11 F0index=find(FF4k==ite); if ~isempty(F0index) tmpMat=F3(F0index); tmpSco=sum(tmpMat); ScoreBin(ite)=mod(tmpSco,300); end end Scorek(k)=sum(ScoreBin); end ScoreN=ScoreN-Scorek此代码为何无法运行？
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