yichuansuanfa.txt

这是一个关于遗传算法的MATLAB程序,用于求某种函数的极值

%Generic Alogorithm for function f(x1,x2) optimum
clear all;
close all;

%Parameters
Size=80;
G=100;
Codel=10;

umax=2.048;
umin=-2.048;

E=round(rand(Size,2*Codel));

%Main Program
for k=1:1:G
time(k)=k;

for s=1:Size
m=E(s,:);
y1=0;
y2=0;

%Uncoding
m1=m(1:1:Codel);
for i=1:1:Codel
	y1=y1+m1(i)*2^(i-1);
end
x1=(umax-umin)*y1/1023+umin;
m2=m(Codel+1:1:2*Codel);
for i=1:1:Codel
	y2=y2+m2(i)*2^(i-1);
end
x2=(umax-umin)*y2/1023+umin;


F(s)=100*(x1^2-x2)^2+(1-x1)^2;
end 

Ji=1./F;
%**********Step 1 :Evaluate BestJ*******
BestJ(k)=min(Ji);

fi=F;
[Oderfi,Indexfi]=sort(fi);
Bestfi=Oderfi(Size);
BestS=E(Indexfi(Size),:);
bfi(k)=Bestfi;

%******Step 2 : Select and Reproduct Operation*******
fi_sum=sum(fi);
fi_Size=(Oderfi/fi_sum)*Size;

fi_S=floor(fi_Size);

kk=1;
for i=1:1:Size
	for j=1:1:fi_S(i)
	TempE(kk,:)=E(Indexfi(i),:);
  	kk=kk+1;
	end
end

%*******Step 3 : Crossover Operation********
pc=0.60;
n=ceil(20*rand);
for i=1:2:(Size-1)
	temp=rand;
	if pc>temp
	for j=n:1:20
		TempE(i,j)=E(i+1,j);
		TempE(i+1,j)=E(i,j);
	end
	end
end
TempE(Size,:)=BestS;
E=TempE;

%**********step 4 :Mutation Operation*******
%pm=0.001;
%pm=0.001-[1:1:Size]*(0.001)/Size;
%pm=0.0;
pm=0.1;

for i=1:1:Size
for j=1:1:2*Codel
	temp=rand;
	if pm>temp
	if TempE(i,j)==0
	TempE(i,j)=1;
	else
	TempE(i,j)=0;
	end
	end 
end
end

%Guarantee TeepPop(30, : ) is the code belong to the best individual(max(fi))
TempE(Size,:)=BestS;
E=TempE;
end

Max_Value=Bestfi
BestS
x1
x2
figure(1);
plot(time,BestJ);
title('目标函数J的优化过程')
xlabel('Times');
ylabel('Best J');
grid on;
figure(2);
plot(time,bfi);
title('适应度函数F的优化过程')
xlabel('times');
ylabel('Best F');
grid on;