模拟退火算法及禁忌搜索算法的matlab源程序.doc

%%% 模拟退火算法源程序
% 此题以中国31省会城市的最短旅行路径为例:
% clear;clc;
function [MinD,BestPath]=MainAneal(pn)
% CityPosition存储的为每个城市的二维坐标x和y;
CityPosition=[1304 2312;3639 1315;4177 2244;3712 1399;3488 1535;3326 1556;3238 1229;...
4196 1044;4312 790;4386 570;3007 1970;2562 1756;2788 1491;2381 1676;...
1332 695;3715 1678;3918 2179;4061 2370;3780 2212;3676 2578;4029 2838;...
4263 2931;3429 1908;3507 2376;3394 2643;3439 3201;2935 3240;3140 3550;...
2545 2357;2778 2826;2370 2975];
figure(1);
plot(CityPosition(:,1),CityPosition(:,2),'o')
m=size(CityPosition,1);%城市的数目
%
D = sqrt((CityPosition(:,ones(1,m)) - CityPosition(:,ones(1,m))').^2 + ...
(CityPosition(:,2*ones(1,m)) - CityPosition(:,2*ones(1,m))').^2);
path=zeros(pn,m);
for i=1:pn
path(i,:)=randperm(m);
end
iter_max=100;%i
m_max=5;%
Len1=zeros(1,pn);Len2=zeros(1,pn);path2=zeros(pn,m);
t=zeros(1,pn);
T=1e5; tau=1e-5;
N=1;
while T>=tau
iter_num=1;
m_num=1;
while m_num<m_max && iter_num<iter_max
for i=1:pn
Len1(i)=sum([D(path(i,1:m-1)+m*(path(i,2:m)-1)) D(path(i,m)+m*(path(i,1)-1))]);
path2(i,:)=ChangePath2(path(i,:),m);
Len2(i)=sum([D(path2(i,1:m-1)+m*(path2(i,2:m)-1)) D(path2(i,m)+m*(path2(i,1)-1))]);
end
R=rand(1,pn);
if find((Len2-Len1<t&exp((Len1-Len2)/T)>R)~=0)
path(find((Len2-Len1<t&exp((Len1-Len2)/T)>R)~=0),:)=path2(find((Len2-Len1<t&exp((Len1-Len2)/T)>R)~=0),:); %#ok<FNDSB>
Len1(f