aga.m

来自「自适应遗传算法的基础结构」· M 代码 · 共 51 行

figure(1);
fplot('v.*sin(10*pi*v)+2.0',[-1,2]);
NIND=40;
MAXGEN=30;
PRECI=20;
GGAP=0.9;
trace=zeros(2,MAXGEN);
FieldD=[20;-1;2;1;0;1;1];
Chrom=crtbp(NIND,PRECI);
gen=0;
v=bs2rv(Chrom,FieldD);
ObjV=v.*sin(10*pi*v)+2.0;
while gen<MAXGEN,
   FitnV=ranking(-ObjV);
   SelCh=select('sus',Chrom,FitnV,GGAP);
   FitnVmax=max(FitnV);
   FitnVave=sum(FitnV)/NIND;
     if(FitnV>= FitnVave)
        Index1=find(FitnV>= FitnVave);
        Index2=find(FitnV< FitnVave);
        Pc1=0.5*(FitnVmax- FitnV(Index,1))/(FitnVmax- FitnVave);
        Pm1=0.02*(FitnVmax- FitnV(Index,1))/(FitnVmax- FitnVave);
    else    
        Pc2=0.85;
        Pm2=0.05;
   end 
 %end 
   SelCh=recombin('xovsp',SelCh(Index1,1),Pc1);
   SelCh=recombin('xovsp',SelCh(Index2,1),Pc2);
   SelCh=mut(SelCh(Index1,1),Pm1);
   SelCh=mut(SelCh(Index2,1),Pm2);
   v=bs2rv(SelCh,FieldD);
   ObjVSel=v.*sin(10*pi*v)+2.0;
   [Chrom ObjV]=reins(Chrom,SelCh,1,1,ObjV,ObjVSel);
   gen=gen+1;
   variable=bs2rv(Chrom, FieldD)
   [Y,I]=max(ObjV),hold on;
   plot(I,Y,'bo');
   trace(1,gen)=max(ObjV);
   trace(2,gen)=sum(ObjV)/length(ObjV);
   if (gen==20)
       figure(2);
       plot(ObjV);hold on;
       plot(ObjV,'b*');grid;
   end
end
figure(3);
plot(trace(1,:)','Pr');
hold on;
plot(trace(2,:)','-.');grid;
legend('解的变化','种群均值的变化')