VRP遗传算法的Matlab代码.rar

%OX顺序交叉策略 Pc=0.9; for i=1:2:N [n,m]=size(pop); while n>=20 break; end cross_P=rand; %随机产生一个数，以比较交叉概率 if cross_P<=Pc %交叉概率为Pc P1=pop(i,:); P2=pop(i+1,:); X=floor(rand*k)+2; Y=floor(rand*k)+2; if X<Y change1=P1(X:Y); change2=P2(X:Y); %开始修复 Order Crossover %1.列出基因 p1=[P1(Y+1:end),P1(1:X-1),change1]; p2=[P2(Y+1:end),P2(1:X-1),change2]; %2.1删除已由基因 P1 for j=1:length(change2) p1(p1==change2(j))=[]; end %2.2删除已由基因 P2 for j=1:length(change1) p2(p2==change1(j))=[]; end %3.1修复 P1 P1=[p1(k+3-Y+1:end),change2,p1(1:k+3-Y)]; %3.1修复 P2 P2=[p2(k+3-Y+1:end),change1,p2(1:k+3-Y)]; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% else change1=P1(Y:X); change2=P2(Y:X); %开始修复 Order Crossover %1.列出基因 p1=[P1(X+1:end),P1(1:Y-1),change1]; p2=[P2(X+1:end),P2(1:Y-1),change2]; %2.1删除已由基因 P1 for j=1:length(change2) p1(p1==change2(j))=[]; end %2.2删除已由基因 P2 for j=1:length(change1) p2(p2==change1(j))=[]; end %3.1修复 P1 P1=[p1(k+3-X+1:end),change2,p1(1:k+3-X)]; %3.1修复 P2 P2=[p2(k+3-X+1:end),change1,p2(1:k+3-X)]; [np1,mp1]=size(P1); [np2,mp2]=size(P2); if mp1==9 P1=[0,P1,0]; end if mp2==9 P2=[0,P2,0]; end P1=adjust(P1); P2=adjust(P2); P1=adjust(P1); P2=adjust(P2); end end new_pop=[pop;P1;P2]; pop=new_pop; end clear X; clear Y; clear i; clear j; clear f; clear I;