MATLAB遗传算法VRP

function [R,minlen]=geneticVRP(D,dis,demand,volume,n,C,m,Pc,Pm) [N,NN]=size(D); farm=zeros(n,N);%用于存储种群 for i=1:n farm(i,:)=randperm(N); end R=farm(1,:);%一个随机解(个体) len=zeros(n,1);%存储路径长度 counter=1; while counter<=C counter %==================================================================== %=====================交叉操作======================== FARM=farm; FARM2=FARM; [aa,bb]=size(FARM); for i=1:2:aa if Pc>rand&&i<aa %交叉概率Pc A=FARM(i,:); B=FARM(i+1,:); [A,B]=intercross(A,B); FARM(i,:)=A; FARM(i+1,:)=B; end end % 交叉检验 (可省去) fitness_value_c=zeros(1,1);%子代适应值 for i=1:aa if fitness(demand,FARM(i,:),volume,dis,fitness_value_c,D)>fitness(demand,FARM2(i,:),volume,dis,fitness_value_c,D) FARM(i,:)=FARM2(i,:); end end clear aa; clear bb; clear A; clear B; clear fitness_value_c; %=================================================================== %========================变异========================= % FARM2=FARM; [aa,bb]=size(FARM); %aa=nn2 for i=1:aa if Pm>=rand FARM(i,:)=mutate(FARM(i,:)); end end % 变异检验(可省略) % fitness_value_c=zeros(1,1);%子代适应值 % for i=1:aa % if fitness(demand,FARM(i,:),volume,dis,fitness_value_c,D)>fitness(demand,FARM2(i,:),volume,dis,fitness_value_c,D) % FARM(i,:)=FARM2(i,:); % end % end clear aa; clear bb; %=================================================================== %=====================群体的选择和更新====================== farm=FARM; [c,d]=size(farm); fitness_value_c=zeros(c,1);%子代适应值 [fitness_value_c]=fitness(demand,farm,volume,dis,fitness_value_c,D); %求个体的适应度 %淘汰子代 [a,b]=sort(fitness_value_c); [u,i]=size(fitness_value_c); for i=1:u farm(i,:)=FARM(b(i),:); end minlen=a(1); R=farm(1,:) ; %更新最短路径 farm(c-19:c,:)=farm(1:20,:); % %画图 hold on plot(counter,minlen,'-b*'); hold off; counter=counter+1; % Rlength=myLength(D,R,volume); % %不会画图！！！ % % subplot(2,1,1) % % plot(counter,Rlength,'-ro') % % hold on % % plot(counter,myLength(D,R),':b*') % % hold off; % hold on % plot(counter,minlen,'-b*'); % hold off; end %结果输出 minlen R output_fitness(demand,R,volume,dis,fitness_value_c,D); % subplot(2,1,1) % plot(R,'-ro')