遗传算法求解0-1背包问题matlab代码.zip

% % @作者：随心390 % @微信公众号：优化算法交流地 % clear clc %% 创建数据 % value=[3,4,9,15,2,4,6,8,10,2.5,5,7,10,12,3,3,5,10,10,2]; %20个物品的价值 % weight=[10,13,24,32,4,12,15,22,26,5.2,14,18,25,28,6.8,14,14,28,32,6.8]; %20个物品的重量 % cap=92; %每个背包的装载量为92 value=[200,208,198,192,180,180,168,176,182,168,187,138,184,154,168,175,198,... 184,158,148,174,135, 126,156,123,145,164,145,134,164,134,174,102,149,134,... 156,172,164,101,154,192,180,180,165,162,160,158,155, 130,125]; weight=[80,82,85,70,72,70,82,75,78,45,49,76,45,35,94,49,76,79,84,74,76,63,... 35,26,52,12,56,78,16,52, 16,42,18,46,39,80,41,41,16,35,70,72,70,66,50,55,25, 50,55,40]; cap=1000; %每个背包的装载量为92 N=length(value); %物品个数 %% 参数设置 NIND=500; %种群大小 MAXGEN=500; %迭代次数 Pc=0.8; %交叉概率 Pm=0.03; %变异概率 GGAP=0.9; %代沟(Generation gap) %% 初始化种群 Chrom=InitPop(NIND,N,weight,cap); %% 优化 gen=0; figure; hold on;box on xlim([0,MAXGEN]) title('优化过程') xlabel('代数') ylabel('最优值') ObjV=allValue(Chrom,value,weight); %计算每个染色体的物品总价值 preObjV=max(ObjV); while gen<MAXGEN %计算适应度 ObjV=allValue(Chrom,value,weight); %计算每个染色体的物品总价值 line([gen-1,gen],[preObjV,max(ObjV)]);pause(0.0001) preObjV=max(ObjV); FitnV=ObjV; %选择 SelCh=Select(Chrom,FitnV,GGAP); %交叉操作 SelCh=Recombin(SelCh,Pc); %变异 SelCh=Mutate(SelCh,Pm); %重插入子代的新种群 Chrom=Reins(Chrom,SelCh,ObjV); %调整种群染色体,将不满足载重量约束的染色体进行调整 Chrom=adjustChrom(Chrom,weight,cap); %更新迭代次数 gen=gen+1 ; end %% 找出最优解 ObjV=allValue(Chrom,value,weight); %计算每个染色体的物品总价值 [maxObjV,maxInd]=max(ObjV); bestChrom=Chrom(maxInd,:); [sumV,sumW]=chromVW(N,bestChrom,value,weight); best=[0,0,0,0,0,0,0,0,0,1,1,0,1,1,0,1,0,0,0,0,0,0,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,1,1,1,1,0,1]; [sumBV,sumBW]=chromVW(N,best,value,weight);