matlab、lingo程序代码3-背包问题(遗传算法)复习过程

背包问题---遗传算法解决
function Population1=GA_copy(Population,p,w0,w)
%复制算子
%Population为种群
n=length(Population(:,1));
fvalue=zeros(1,n);
for i=1:n
fvalue(i)=GA_beibao_fitnessvalue(Population(i,:),p,w0,w);
end
fval=fvalue/sum(fvalue);
F(1)=0;
for j=1:n
F(j+1)=0;
for k=1:j
F(j+1)=F(j+1)+fval(k);
end
end
for i=1:n
test=rand;
for j=1:n
if((test>=F(j))&&(test<F(j+1)))
Population1(i,:)=Population(j,:);
end
end
end
function Population1=GA_exchange(Population,pc) %遗传算法交换算子
%pc为交换概率
Population1=Population;
POP=[];
n=length(Population(:,1));
%k=floor(n*pc); %用于交换的染色体数目
%采用单点交换算子
j=1;
l=length(Population(1,:));
for i=1:n
test(i)=rand;
if test(i)<pc
for z=1:l
POP(j,z)=Population(i,z);
end
POP(j,l+1)=i;
p(j)=randint(1,1,[1 l-1]);
j=j+1;
end
end
k0=j-1;
k=floor(k0/2);
if k>=1
for m=1:k
for t=p(2*m-1)+1:l
s=POP(2*m-1,t);
POP(2*m-1,t)=POP(2*m,t);
POP(2*m,t)=s;
end
end
for m=1:k0
for i=1:l
Population1(POP(m,l+1),i)=POP(m,i);
end
end
end
function fitnessvalue=GA_fitnessvalue(x,p,w0,w) %使用惩罚法计算适应度值
%x为染色体
%p为背包问题中每个被选物体的价值
%w0为背包问题中背包总容积
%w为背包问题中每个被选物品的容积
l=length(x);
for i=1:l
a(i)=p(i).*x(i);
end
f=sum(a);
b=min(w0,abs(sum(w)-w0));
for i=1:l
wx(i)=w(i).*x(i);
end
if abs(sum(wx)-w0)>b*0.99
p=0.99;
else
p=abs(sum(wx)-w0)/b;
end
fitnessvalue=f*(1-p)*(1-p)*(1-p);
function Population=GA_Initial(n,P)
%n为染色体长度，即所供选择的物品总数
%P为初始种群大小
for i=1:P
for j=1:n
temp=rands(1,1);
if temp>0
Population(i,j)=1;
else
Population(i,j)=0;
end
end
end
function Population1=GA_tubian(Population,pe_tubian) %遗传算法突变算子
%pe为突变概率
Population1=Population;
n=length(Population(:,1));
m=length(Population(1,:));
for i=1:n
for j=1:m
test=rand;
if test<pe_tubian
Population1(i,j)=1-Population1(i,j);
end
end
end。