多目标遗传算法_供应商选择附matlab代码.zip

%项目名称：多目标遗传算法求解供应商选择问题 %% %输出 %最优解ParetoBest %最优目标值Pareto_Obj clc;close all;clear; load Price;load R;k=1; Sum_Demand=4000;Nmin=2; %需求总量Sum_Demand %规定的最少供应商数目Nmin %计算的权重R %表1 候选服务供应商的价格情况 %========================================================================== Pop_num=10;Max_gen=50;Pc=0.7;Pm=0.1; %种群规模Pop_num %最大迭代次数Max_gen %交叉概率Pc %变异概率Pm %========================================================================== tic MMin=zeros(Max_gen,Nmin);AAvg=zeros(Max_gen,Nmin);MMax=zeros(Max_gen,Nmin); Obj=[];H=[];T_size=size(Price,1); Pop=Init_Pop(Price,Sum_Demand,Pop_num,Nmin); for i=1:Pop_num [X1,X2]=Decode(Pop(i,:),R,Price,Sum_Demand); Pop(i,:)=X1; Obj(i,:)=Evaluation(X1,X2,Price,R); end Q_Obj=pareto(Obj,Pop_num); Q_Obj_num=size(Q_Obj,1); Q_Obj_pos= findrow(Obj,Q_Obj); Q=zeros(Q_Obj_num,T_size); for i=1:Q_Obj_num Q(i,:)=Pop(Q_Obj_pos(i),:); end while k<=Max_gen [Cross_Pop]=Mating_pool(Pop_num,Pop,Pc,Price,Sum_Demand,Nmin); [Mut_Pop]=Mutation(Cross_Pop,Price,Pm,Sum_Demand,Nmin); Y_Pop=[]; Y_Pop=[Pop;Mut_Pop]; Y_Pop_num=size(Y_Pop,1); Obj1=[]; for i=1:Y_Pop_num [X1,X2]=Decode(Y_Pop(i,:),R,Price,Sum_Demand); Y_Pop(i,:)=X1; Obj1(i,:)=Evaluation(X1,X2,Price,R); end %更新外部档案解 Y_Pop=[Q;Y_Pop]; Obj1=[Q_Obj;Obj1]; Y_Pop_num=size(Y_Pop,1); Q_Obj1=[]; Q_Obj1=pareto(Obj1,Y_Pop_num); Q_Obj1_num=size(Q_Obj1,1); Q_Obj1_pos= findrow(Obj1,Q_Obj1); Q_Obj=[];Q=zeros(Q_Obj1_num,T_size); Q_Obj=Q_Obj1; for i=1:Q_Obj1_num Q(i,:)=Y_Pop(Q_Obj1_pos(i),:); %外部档案非劣解Q,外部档案非劣解的目标值Q_Obj end %====================================================================== %计算最大最小平均值 outfile_Obj=Q_Obj; outfile=Q; outfile_num=size(outfile,1); if outfile_num==1 Min_Q_Obj=outfile_Obj; Max_Q_Obj=outfile_Obj; Avg_Q_Obj=outfile_Obj; else Min_Q_Obj=min(outfile_Obj); Max_Q_Obj=max(outfile_Obj); Avg_Q_Obj=sum(outfile_Obj)/size(outfile_Obj,1); end MMin(k,:)=Min_Q_Obj; MMax(k,:)=Max_Q_Obj; AAvg(k,:)=Avg_Q_Obj; %====================================================================== %更新种群 L_Q=Q; Q_num=size(L_Q,1); if Q_num<Pop_num y=Pop_num-Q_num; for i=1:y h_Pop=Copy_of_Init_Pop(Price,Sum_Demand,Nmin); L_Q=[L_Q;h_Pop]; end Q_Obj_pos=1:Q_num;%% else r_num=randperm(Q_num); r_num(Pop_num+1:end)=[]; Y_Q=L_Q(r_num,:); L_Q=Y_Q; Q_Obj_pos=1:Pop_num;%% end Pop=L_Q; k=k+1 end for i=1:size(Q,1) [X1,X2]=Decode(Q(i,:),R,Price,Sum_Demand); Pareto_Best(i,:)=[X1,X2]; Pareto_Obj(i,:)=Evaluation(X1,X2,Price,R); end t=toc x=1:Max_gen; plot(x,MMin(:,1),'r-');hold on %plot(x,AAvg(:,1),'b--');hold on %plot(x,MMax(:,1),'k:');hold on figure(2) plot(x,MMin(:,2));hold on %plot(x,AAvg(:,2));hold on %plot(x,MMax(:,2));hold on