Matlab多目标优化遗传算法源程序很好的应用案例.zip_matlab遗传算法_多目标优化_遗传算法 _遗传算法 matlab

function [pop,objective]=decoding(pop,oldpop) % 解码操作，先修复不可行解，再计算目标值。 global popsize L x=zeros(popsize,1); y=zeros(popsize,1); for i=1:popsize x(i)=bin2dec(pop(i,1:L/2)); y(i)=bin2dec(pop(i,L/2+1:end)); % x、y和小于100， 且均不为零 if x(i)+y(i)>99 switch 1 case x(i)>98&y(i)>98 pop(i,:)=oldpop(i,:); x(i)=bin2dec(pop(i,1:L/2)); y(i)=bin2dec(pop(i,L/2+1:end)); case x(i)>98&y(i)<=98 x(i)=ceil(rand*(99-y(i))); a=dec2bin([x(i),100]); pop(i,1:L/2)=a(1,:); case x(i)<=98&y(i)>98 y(i)=ceil(rand*(99-x(i))); a=dec2bin([y(i),100]); pop(i,L/2+1:end)=a(1,:); otherwise if rand<0.5 x(i)=ceil(rand*(99-y(i))); a=dec2bin([x(i),100]); pop(i,1:L/2)=a(1,:); else y(i)=ceil(rand*(99-x(i))); a=dec2bin([y(i),100]); pop(i,L/2+1:end)=a(1,:); end end end if x(i)*y(i)==0 switch 1 case x(i)==0&y(i)~=0&y(i)~=99 x(i)=ceil(rand*(99-y(i))); a=dec2bin([x(i),100]); pop(i,1:L/2)=a(1,:); case y(i)==0&x(i)~=0&x(i)~=99 y(i)=ceil(rand*(99-x(i))); a=dec2bin([y(i),100]); pop(i,L/2+1:end)=a(1,:); otherwise pop(i,:)=oldpop(i,:); x(i)=bin2dec(pop(i,1:L/2)); y(i)=bin2dec(pop(i,L/2+1:end)); end end end objective=[300./x+500./y+300./(100-x-y),30*(300./x-3)+12*(500./y-5)+(300./(100-x-y)-3)];