%generic algorithm for function f(x1,x2) optimum
% function main(pc1,pm1)
clear all
close all
% parameters
size=30;
generation=500;
codel=12;
pc1=0.8;
pm1=0.01;
pc=pc1;
pm=pm1;
umax=2.048;
umin=-2.048;
E=round(rand(size,2*codel)); %initial code
% main program
for k=1:generation
time(k)=k;
for s=1:size
m=E(s,:);
y1=0;
y2=0;
% uncoding
m1=m(1:1:codel);
for i=1:codel
y1=y1+m1(i)*2^(i-1);
end
x1=(umax-umin)*y1/2^codel+umin;
m2=m(codel+1:1:2*codel);
for i=1:codel
y2=y2+m2(i)*2^(i-1);
end
x2=(umax-umin)*y2/2^codel+umin;
F(s)=100*(x1^2-x2)^2+(1-x1)^2; %Calculate the fitness
end
%Ji=1./F
BestJ(k)=min(F);
tempf=min(F);
if abs(tempf)<0.002
break;
end
Ji=F+1.0e-10;
fi=1./Ji; %由于要进行复制，适应度函数取反，最小值则复制个数最多
[oderfi,indexfi]=sort(fi); % arranging fi small to bigger
Bestfi=oderfi(size); %let bestfi=max(fi)
BestS=E(indexfi(size),:); % find the best individual
bfi(k)=Bestfi; % record the best fi to show in the figure
%select and reproduct operation
fi_sum=sum(fi);
fi_size=(oderfi/fi_sum)*size;
fi_s=floor(fi_size); % 取整，selecting bigger fi value
kk=1;
for i=1:size
for j=1:fi_s(i)
tempe(kk,:)=E(indexfi(i),:);
kk=kk+1; %kk is used to reproduce
end
end
%crossover operation
n=ceil(2*codel*rand);
for i=1:2:(size-1)
temp=rand;
if pc>temp
for j=n:1:2*codel
tempe(i,j)=E(i+1,j);
tempe(i+1,j)=E(i,j);
end
end
end
tempe(size,:)=BestS; % the last to save the best one
E=tempe;
%mutation operation
pm=0.2;
for i=1:size
for j=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 tempPop(30,:) is the code belong to the best individual (max(fi))
tempe(size,:)=BestS;
E=tempe;
%max_value=Bestfi;
BestS
%Bestfi
x1
x2
temp=100*(x1^2-x2)^2+(1-x1)^2
k
tempf
