求一个TSP的matlab程序

蚂蚁算法实现tsp。其中city是n行2列的矩阵，表示n个城市的经纬度，iter_max是最大循环次数，其余是蚂蚁算法的参数。

function [Shortest_Route,Shortest_Length]=anttsp(city,iter_max,m,Alpha,Beta,Rho,Q)

n=size(city,1)

d=zeros(n,n)

d=squareform(pdist(city))

Eta=1./d

Tau=ones(n,n)

Tabu=zeros(m,n)

nC=1

R_best=zeros(iter_max,n)

L_best=inf.*ones(iter_max,1)

while nC<=iter_max

route=[]

for i=1:ceil(m/n)

route=[route,randperm(n)]

end

Tabu(:,1)=(route(1,1:m))'

for j=2:n

for i=1:m

visited=Tabu(i,1:(j-1))

J=zeros(1,(n-j+1))

P=J

Jc=1

for k=1:n

if isempty(find(visited==k, 1))

J(Jc)=k

Jc=Jc+1

end

end

for k=1:length(J)

P(k)=(Tau(visited(end),J(k))^Alpha)*(Eta(visited(end),J(k))^Beta)

end

P=P/(sum(P))

Pcum=cumsum(P)

Select=find(Pcum>=rand)

if isempty(Select)%是不是一定能保证Select不为空

Tabu(i,j)=round(1+(n-1)*rand)

else

next_visit=J(Select(1))

Tabu(i,j)=next_visit

end

end

end

if nC>=2

Tabu(1,:)=R_best(nC-1,:)

end

L=zeros(m,1)

for i=1:m

R=Tabu(i,:)

for j=1:(n-1)

L(i)=L(i)+d(R(j),R(j+1))

end

L(i)=L(i)+d(R(1),R(n))

end

L_best(nC)=min(L)

pos=find(L==L_best(nC))

R_best(nC,:)=Tabu(pos(1),:)

nC=nC+1

Delta_Tau=zeros(n,n)

for i=1:m

for j=1:(n-1)

Delta_Tau(Tabu(i,j),Tabu(i,j+1))=Delta_Tau(Tabu(i,j),Tabu(i,j+1))+Q/L(i)

end

Delta_Tau(Tabu(i,n),Tabu(i,1))=Delta_Tau(Tabu(i,n),Tabu(i,1))+Q/L(i)

end

Tau=(1-Rho).*Tau+Delta_Tau

Tabu=zeros(m,n)

end

Pos=find(L_best==min(L_best))

Shortest_Route=R_best(Pos(1),:)

Shortest_Length=L_best(Pos(1))

end

因为是专业论文，译者不知是否准确。请你以专业方面的知识来修正。

Vehicle Routing was first studied in 1959 and soon attracted a rang of experts did researches in the operations research, management, computer applications, combinatorics, graph theory, etc. The findings have been widely used in the transport system, logistics and distribution system, express transceiver systems. This article will start from the vehicles in general, set up a mathematical model, introduced the issue of Vehicle Routing in practical application and academic research produced a number of different extension and style changes. Focus on the extension study on business travels, and finally through the Ant algorithm, using MATLAB programming to solve practical problems to achieve the optimal route. Because Ant algorithm is of a search of the probability, the computation results are generally inclined to a convergence of values. Through multiple iterations experiment, it can obtain the Optimum Solution.

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