cputime=0;tic;
clc;clear all
%定义遗传算法
NIND=200; %个体数目(Number of individuals)
MAXGEN=100; %最大遗传代数(Maximum number of generations)
NVAR=2; %变量个数
PRECI=20; %变量的二进制位数(Precision of variables)
GGAP=0.9; %代沟(Generation gap)
trace1=[];trace2=[];trace3=[]; %性能跟踪
%建立区域描述器(Build field descriptor)
FieldD=[rep([PRECI],[1,NVAR]);[1,1;4,2];rep([1;0;1;1],[1,NVAR])];
Chrom=crtbp(NIND,NVAR*PRECI); %初始种群
x=bs2rv(Chrom,FieldD); %初始种群十进制转换
gen=1;
while gen<MAXGEN
[NIND, N]=size(Chrom);
M=fix(NIND/2);
ObjV1=gafun1(x(1:M,:)); %分组后第一目标函数值
FitnV1=ranking(ObjV1'); %分配适应度值(Assign fitness values)
SelCh1=select('sus',Chrom(1:M,:),FitnV1,GGAP); %选择
ObjV2=gafun2(x(M+1:NIND,:)); %分组后第二目标函数值
FitnV2=ranking(ObjV2');
SelCh2=select('sus',Chrom((M+1):NIND,:),FitnV2,GGAP); %选择
SelCh=[SelCh1;SelCh2]; %合并
SelCh=recombin('xovsp',SelCh,0.7); %重组
Chrom=mut(SelCh); %变异
x=bs2rv(SelCh,FieldD);
trace1(gen,1)=min(gafun1(x));
trace1(gen,2)=sum(gafun1(x))/length(gafun1(x));
trace2(gen,1)=min(gafun2(x));
trace2(gen,2)=sum(gafun2(x))/length(gafun2(x));
trace3(gen,1)=min(gafun1(x)+gafun2(x));
trace3(gen,2)=sum(gafun1(x))/length(gafun1(x))+sum(gafun2(x))/length(gafun2(x));
gen=gen+1;
[Y1, I1]=min(ObjV1);
x1=bs2rv(Chrom(I1,:),FieldD);
[Y2, I2]=min(ObjV2);
x2=bs2rv(Chrom(I2,:),FieldD);
end
figure(1);clf;
plot(trace1(:,1));hold on;plot(trace1(:,2),'-.');
plot(trace1(:,1),'.');plot(trace1(:,2),'.');grid;
legend('解的变化','种群均值的变化')
xlabel('迭代次数');ylabel('第一目标函数值');
figure(2);clf;
plot(trace2(:,1));hold on;
plot(trace2(:,2),'-.');
plot(trace2(:,1),'.');
plot(trace2(:,2),'.');grid;
legend('解的变化','种群均值的变化')
xlabel('迭代次数');ylabel('第二目标函数值');
figure(3);clf;
plot(trace3(:,1));hold on;
plot(trace3(:,2),'-.');
plot(trace3(:,1),'.');
plot(trace3(:,2),'.');grid;
legend('解的变化','种群均值的变化')
xlabel('迭代次数');ylabel('目标函数值之和');
figure(4);clf;plot(gafun1(x));hold on;
plot(gafun2(x),'r-.');grid;
x1,Y1,x2,Y2
x0=[1.0150 1.5126];
f(1)=(x0(1).^2+x0(2).^2)*0.25
f(2)=2*x0(1)*(1-x0(2))
toc;
cputime=toc;
