nonlinearrankselect.m

继续上次传的遗传算法

function [selectpop]=NonlinearRankSelect(pop,LB,UB) 
[m,n]=size(pop);
selectpop=zeros(m,n);
fit=zeros(m,1);
for i=1:m
    fit(i)=fun(b2f(pop(i,:),LB,UB));
end
fitness=fit/sum(fit);
for i=2:m
    fitness(i)= fitness(i-1)+fitness(i);
end
rnums=rand(m,1);
for i=1:m
    for j=1:m
        if rnums(i)<=fitness(j)
            selectpop(i,:)=pop(j,:);
    


selectprob=fit/sum(fit);

q=max(selectprob);%选择最优的概率
x=zeros(m,2);
x(:,1)=[m:-1:1]';
[y x(:,2)]=sort(selectprob);
r=q/(1-(1-q)^m);%标准分布基值
newfit(x(:,2))=r*(1-q).^(x(:,1)-1);%生成选择概率
newfit=cumsum(newfit);%计算各选择概率之和
rNums=sort(rand(m,1));
fitIn=1;newIn=1;
while newIn<=m
    if rNums(newIn)<newfit(fitIn)
        selectpop(newIn,:)=pop(fitIn,:);
        newIn=newIn+1;
    else
        fitIn=fitIn+1;
    end
end