关于旅行商问题代码

%粒子群算法求解旅行商问题

% By lReij

close all;

clear all;

PopSize=500;%种群大小

CityNum = 14;%城市数

OldBestFitness=0;%旧的最优适应度值

Iteration=0;%迭代次数

MaxIteration =2000;%最大迭代次数

IsStop=0;%程序停止标志

Num=0;%取得相同适应度值的迭代次数

c1=0.5;%认知系数

c2=0.7;%社会学习系数

w=0.96-Iteration/MaxIteration;%惯性系数,随迭代次数增加而递减

%节点坐标

node=[16.47 96.10; 16.47 94.44; 20.09 92.54; 22.39 93.37; 25.23 97.24;...

22.00 96.05; 20.47 97.02; 17.20 96.29; 16.30 97.38; 14.05 98.12;...

16.53 97.38; 21.52 95.59; 19.41 97.13; 20.09 94.55];

%初始化各粒子，即产生路径种群

Group=ones(CityNum,PopSize);

for i=1:PopSize

Group(:,i)=randperm(CityNum)';

end

Group=Arrange(Group);

%初始化粒子速度（即交换序）

Velocity =zeros(CityNum,PopSize);

for i=1:PopSize

Velocity(:,i)=round(rand(1,CityNum)'*CityNum); %round取整

end

%计算每个城市之间的距离

CityBetweenDistance=zeros(CityNum,CityNum);

for i=1:CityNum

for j=1:CityNum

CityBetweenDistance(i,j)=sqrt((node(i,1)-node(j,1))^2+(node(i,2)-node(j,2))^2); end

end

%计算每条路径的距离

for i=1:PopSize

EachPathDis(i) = PathDistance(Group(:,i)',CityBetweenDistance);

end

IndivdualBest=Group;%记录各粒子的个体极值点位置,即个体找到的最短路径IndivdualBestFitness=EachPathDis;%记录最佳适应度值,即个体找到的最短路径的长度[GlobalBestFitness,index]=min(EachPathDis);%找出全局最优值和相应序号

%初始随机解

figure;

subplot(2,2,1);

PathPlot(node,CityNum,index,IndivdualBest);

title('随机解');

%寻优

while(IsStop == 0) & (Iteration < MaxIteration)

%迭代次数递增

Iteration = Iteration +1;

%更新全局极值点位置,这里指路径

for i=1:PopSize

GlobalBest(:,i) = Group(:,index);

end

%求pij-xij ,pgj-xij交换序，并以概率c1，c2的保留交换序

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保留上一代交换序

Velocity=HoldByOdds(Velocity,w);

Group = PathExchange(Group,Velocity); %根据交换序进行路径交换

Group = PathExchange(Group,pij_xij);

Group = PathExchange(Group,pgj_xij);

for i = 1:PopSize % 更新各路径总距离

EachPathDis(i) = PathDistance(Group(:,i)',CityBetweenDistance);

end

IsChange = EachPathDis

IndivdualBestFitness = IndivdualBestFitness.*( ~IsChange) + EachPathDis.*IsChange;%更新个体最佳路径距离

[GlobalBestFitness, index] = min(EachPathDis);%更新全局最佳路径,记录相应的序号

if GlobalBestFitness==OldBestFitness %比较更新前和更新后的适应度值;

Num=Num+1; %相等时记录加一;

else

OldBestFitness=GlobalBestFitness;%不相等时更新适应度值，并记录清零;

Num=0;

end