關(guān)于旅行商問題代碼

%粒子群算法求解旅行商問題%BylReijcloseall;clearall;PopSize=500;%種群大小CityNum=14;%城市數(shù)OldBestFitness=0;%舊的最優(yōu)適應(yīng)度值Iteration=0;%迭代次數(shù)MaxIteration=2000;%最大迭代次數(shù)IsStop=0;%程序停止標(biāo)志Num=0;%取得相同適應(yīng)度值的迭代次數(shù)c1=0.5;%認(rèn)知系數(shù)c2=0.7;%社會(huì)學(xué)習(xí)系數(shù)w=0.96-Iteration/MaxIteration;%慣性系數(shù),隨迭代次數(shù)增加而遞減%節(jié)點(diǎn)坐標(biāo)node=[16.4796.10;16.4794.44;20.0992.54;22.3993.37;25.2397.24;...22.0096.05;20.4797.02;17.2096.29;16.3097.38;14.0598.12;...16.5397.38;21.5295.59;19.4197.13;20.0994.55];%初始化各粒子,即產(chǎn)生路徑種群Group=ones(CityNum,PopSize);fori=1:PopSizeGroup(:,i)=randperm(CityNum)';endGroup=Arrange(Group);%初始化粒子速度(即交換序)Velocity=zeros(CityNum,PopSize);fori=1:PopSizeVelocity(:,i)=round(rand(1,CityNum)'*CityNum);%round取整end%計(jì)算每個(gè)城市之間的距離CityBetweenDistance=zeros(CityNum,CityNum);fori=1:CityNumforj=1:CityNumCityBetweenDistance(i,j)=sqrt((node(i,1)-node(j,1))^2+(node(i,2)-node(j,2))^2);endend%計(jì)算每條路徑的距離fori=1:PopSizeEachPathDis(i)=PathDistance(Group(:,i)',CityBetweenDistance);endIndivdualBest=Group;%記錄各粒子的個(gè)體極值點(diǎn)位置,即個(gè)體找到的最短路徑IndivdualBestFitness=EachPathDis;%記錄最佳適應(yīng)度值,即個(gè)體找到的最短路徑的長度[GlobalBestFitness,index]=min(EachPathDis);%找出全局最優(yōu)值和相應(yīng)序號%初始隨機(jī)解figure;subplot(2,2,1);PathPlot(node,CityNum,index,IndivdualBest);title('隨機(jī)解');%尋優(yōu)while(IsStop==0)&(Iteration<MaxIteration)%迭代次數(shù)遞增Iteration=Iteration+1;%更新全局極值點(diǎn)位置,這里指路徑fori=1:PopSizeGlobalBest(:,i)=Group(:,index);end%求pij-xij,pgj-xij交換序,并以概率c1,c2的保留交換序pij_xij=GenerateChangeNums(Group,IndivdualBest);pij_xij=HoldByOdds(pij_xij,c1);pgj_xij=GenerateChangeNums(Group,GlobalBest);pgj_xij=HoldByOdds(pgj_xij,c2);%以概率w保留上一代交換序Velocity=HoldByOdds(Velocity,w);Group=PathExchange(Group,Velocity);%根據(jù)交換序進(jìn)行路徑交換Group=PathExchange(Group,pij_xij);Group=PathExchange(Group,pgj_xij);fori=1:PopSize%更新各路徑總距離EachPathDis(i)=PathDistance(Group(:,i)',CityBetweenDistance);endIsChange=EachPathDis<IndivdualBestFitness;%更新后的距離優(yōu)于更新前的,記錄序號IndivdualBest(:,find(IsChange))=Group(:,find(IsChange));%更新個(gè)體最佳路徑IndivdualBestFitness=IndivdualBestFitness.*(~IsChange)+EachPathDis.*IsChange;%更新個(gè)體最佳路徑距離[GlobalBestFitness,index]=min(EachPathDis);%更新全局最佳路徑,記錄相應(yīng)的序號ifGlobalBestFitness==OldBestFitness%比較更新前和更新后的適應(yīng)度值;Num=Num+1;%相等時(shí)記錄加一;elseOldBestFitness=GlobalBestFitness;%不相等時(shí)更新適應(yīng)度值,并記錄清零;Num=0;endifNum>=20%多次迭代的適應(yīng)度值相近時(shí)程序停止IsStop=1;endBestFitness(Iteration)=GlobalBestFitness;%每一代的最優(yōu)適應(yīng)度end%最優(yōu)解subplot(2,2,2);PathPlot(node,CityNum,index,IndivdualBest);title('優(yōu)化解');%進(jìn)化曲線subplot(2,2,3);plot((1:Iteration),BestFitness(1:Iteration));gridon;title('進(jìn)化曲線');%最小路徑值GlobalBestFitnessfunctionGroup=Arrange(Group)[xy]=size(Group);[NO1,index]=min(Group',[],2);%找到最小值1fori=1:ypop=Group(:,i);temp1=pop([1:index(i)-1]);temp2=pop([index(i):x]);Group(:,i)=[temp2'temp1']';endfunctionChangeNums=GenerateChangeNums(Group,BestVar);[xy]=size(Group);ChangeNums=zeros(x,y);fori=1:ypop=BestVar(:,i);%從BestVar取出一個(gè)順序pop1=Group(:,i);%從粒子群中取出對應(yīng)的順序forj=1:x%從BestVar的順序中取出一個(gè)序號NoFromBestVar=pop(j);fork=1:x%從對應(yīng)的粒子順序中取出一個(gè)序號NoFromGroup=pop1(k);if(NoFromBestVar==NoFromGroup)&&(j~=k)%兩序號同且不在同一位置ChangeNums(j,i)=k;%交換子pop1(k)=pop1(j);pop1(j)=NoFromGroup;endendendendfunctionHold=HoldByOdds(Hold,Odds)[x,y]=size(Hold);fori=1:xforj=1:yifrand>OddsHold(i,j)=0;endendendfunctionSumDistance=PathDistance(path,CityBetweenDistance)L=length(path);%path為一個(gè)循環(huán)的節(jié)點(diǎn)順序SumDistance=0;fori=1:L-1SumDistance=SumDistance+CityBetweenDistance(path(i),path(i+1));endSumDistance=SumDistance+CityBetweenDistance(path(1),path(L));%加上首尾節(jié)點(diǎn)的距離functionGroup=PathExchange(Group,Index)[xy]=size(Group);fori=1:ya=Index(:,i);%取出其中一組交換序pop=Group(:,i);%取出對應(yīng)的粒子forj=1:x%取出其中一個(gè)交換算子作交換ifa(j)~=0pop1=pop(j);pop(j)=pop(a(j));pop(a(j))=pop1;endendGroup(:,i)=pop;endfunctionPathPlot(