数学建模与数学实验遗传算法以及随机规划.ppt

遗传算法以及基于模拟遗传算法的随机规划遗传算法步骤例2利用遗传算法求解例3利用遗传算法求解多目标非线性规划求解期望值模型例4机会约束规划fork=2:m1hx=h1(k,:);forkk=2:m2ifhx(kk)==0v1(k,:)=v1(k,:);v1(k-1,:)=v1(k-1,:);elsepk=sum(hx(1:kk-1));ifpk==kk-1x=v1(k,:);v1(k,:)=v1(k-1,:);v1(k-1,:)=x;elsev1(k,:)=v1(k,:);v1(k-1,:)=v1(k-1,:);endendendendfork=1:pop_sizefv2(k,:)=duomubiao3(v1(k,:));endfx=fv2(1,:);x=v1(1,:);注意多目标函数的子程序及其生成方式function[f]=duomubiao3(x)fork=1:5xsin(k)=x(k)*sin(k*x(k));endy1=sum(xsin(1:5));ify1=18x10=y1-18;x6=0;elsex6=18-y1;x10=0;endy2=sum(xsin(1:4));ify2=15x11=y2-15;x7=0;elsex7=15-y2;x11=0;endy3=sum(xsin(1:3));ify3=10x12=y3-10;x8=0;elsex8=10-y3;x12=0;endy4=sum(xsin(1:2));ify4=0x13=y4-0;x9=0;elsex9=0-y4;x13=0;endf1=x6;f2=x7;f3=x8;f4=x9+x13;f=[f1,f2,f3,f4];自适应子程序及其表达方式function[v1,x,fx]=shiying3(v,pop_size,x,fx)fv=[];fork=1:pop_sizex=v(k,:);fvx=multobjli1(x);fv=[fv;fvx];endfvv=fv(:,1);v1=[];fv1=[];[m1,m2]=size(fv);k=1;whilekm2-1;ifsum(fv(:,k).^2)==0k=k+1;elsefvv=fv(:,k);k=m2;endendvv=v;fork=1:pop_sizemin1=min(fvv);max1=max(fvv)+1e-6;dk=find(fvvmin1+1e-6);fv1=[fv1;fvv(dk(1),:)];v1=[v1;vv(dk(1),:)];fvv(dk(1))=max1;endfork=1:pop_sizefv(k,:)=multobjli1(v1(k,:));endfxx=fv(1,:);xx=v1(1,:);%挑选最好的染色体;hh1=(fxx-fx);k=1;whilekm2ifhh1(k)==0k=k+1;elseifhh1(k)0fx=fv(1,:);x=v1(1,:);endk=m2;endendfork=1:pop_sizefv2(k,:)=duomubiao3(v1(k,:));endfxx=fv2(1,:);xx=v1(1,:);%挑选最好的染色体;m2=length(fxx);h=fxx-fx;yfx=0;fork=1:m2ifh(k)0h1(k)=1;e