%%% 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:pnpath(i,:)=randperm(m);enditer_max=100;%im_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>=tauiter_num=1;m_num=1;while m_num<m_max && iter_num<iter_maxfor i=1:pnLen1(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))]);endR=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(find((Len2-Len1<t&exp((Len1-Len2)/T)>R)~=0))=Len2(find((Len2-Len1<t&exp((L en1-Len2)/T)>R)~=0));[TempMinD,TempIndex]=min(Len1);TracePath(N,:)=path(TempIndex,:); %#ok<AGROW>Distance(N)=TempMinD; %#ok<AGROW>N=N+1;elsem_num=m_num+1;endenditer_num=iter_num+1;T=T*0.9;end[MinD,Index]=min(Distance);BestPath=TracePath(Index,:);%disp(MinD)%画出路线图figure(2);plot(CityPosition(BestPath(1:end-1),1),CityPosition(BestPath(1:end-1),2),'r*-') ;function p2=ChangePath2(p1,CityNum)while(1)R=unidrnd(CityNum,1,2);if abs(R(1)-R(2)) > 0break;endendI=R(1);J=R(2);if I<Jp2(1:I)=p1(1:I);p2(I+1:J)=p1(J:-1:I+1);p2(J+1:CityNum)=p1(J+1:CityNum);elsep2(1:J-1)=p1(1:J-1);p2(J:I+1)=p1(I+1:-1:J);p2(I:CityNum)=p1(I:CityNum);end%%% 禁忌搜索算法解决TSP问题%此题以中国31省会城市的最短旅行路径为例：%禁忌搜索是对局部领域搜索的一种扩展,是一种全局逐步寻优算法,搜索过程可以接受劣解,有较强的爬山能力.领域结构对收敛性有很大影响。

function [BestShortcut,theMinDistance]=TabuSearchclear;clc;Clist=[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];CityNum=size(Clist,1);%TSP问题的规模,即城市数目dislist=zeros(CityNum);for i=1:CityNumfor j=1:CityNumdislist(i,j)=((Clist(i,1)-Clist(j,1))^2+(Clist(i,2)-Clist(j,2))^2)^0.5; endendTabuList=zeros(CityNum);% (tabu list)TabuLength=round((CityNum*(CityNum-1)/2)^0.5);%禁忌长度(tabu length)Candidates=200;%候选集的个数 (全部领域解个数)CandidateNum=zeros(Candidates,CityNum);%候选解集合S0=randperm(CityNum);%随机产生初始解BSF=S0;BestL=Inf;clf;figure(1);stop = uicontrol('style','toggle','string'…,'stop','background','white');tic;p=1;StopL=80*CityNum;while p<StopLif Candidates>CityNum*(CityNum-1)/2disp('候选解个数不大于n*(n-1)/2!');break;endALong(p)=Fun(dislist,S0);i=1;A=zeros(Candidates,2);while i<=CandidatesM=CityNum*rand(1,2);M=ceil(M);if M(1)~=M(2)A(i,1)=max(M(1),M(2));A(i,2)=min(M(1),M(2));if i==1isa=0;elsefor j=1:i-1if A(i,1)==A(j,1) && A(i,2)==A(j,2)isa=1;break;elseisa=0;endendendif ~isai=i+1;elseendelseendendBestCandidateNum=100;%保留前BestCandidateNum个最好候选解 BestCandidate=Inf*ones(BestCandidateNum,4);F=zeros(1,Candidates);for i=1:CandidatesCandidateNum(i,:)=S0;CandidateNum(i,[A(i,2),A(i,1)])=S0([A(i,1),A(i,2)]); F(i)=Fun(dislist,CandidateNum(i,:));if i<=BestCandidateNumBestCandidate(i,2)=F(i);BestCandidate(i,1)=i;BestCandidate(i,3)=S0(A(i,1));BestCandidate(i,4)=S0(A(i,2));elsefor j=1:BestCandidateNumif F(i)<BestCandidate(j,2)BestCandidate(j,2)=F(i);BestCandidate(j,1)=i;BestCandidate(j,3)=S0(A(i,1));BestCandidate(j,4)=S0(A(i,2));break;endendendend%对BestCandidate[JL,Index]=sort(BestCandidate(:,2));SBest=BestCandidate(Index,:);BestCandidate=SBest;if BestCandidate(1,2)<BestLBestL=BestCandidate(1,2);S0=CandidateNum(BestCandidate(1,1),:);BSF=S0;for m=1:CityNumfor n=1:CityNumif TabuList(m,n)~=0TabuList(m,n)=TabuList(m,n)-1;endendendTabuList(BestCandidate(1,3),BestCandidate(1,4))=TabuLength;elsefori=1:BestCandidateNumif TabuList(BestCandidate(i,3),BestCandidate(i,4))==0S0=CandidateNum(BestCandidate(i,1),:);for m=1:CityNumfor n=1:CityNumif TabuList(m,n)~=0TabuList(m,n)=TabuList(m,n)-1;endendendTabuList(BestCandidate(i,3),BestCandidate(i,4))=TabuLength;break;endendendp=p+1;ArrBestL(p)=BestL; %#ok<AGROW>for i=1:CityNum-1plot([Clist(BSF(i),1),Clist(BSF(i+1),1)],[Clist(BSF(i),2),Clist(BSF(i+1),2)],'bo-');hold on;endplot([Clist(BSF(CityNum),1),Clist(BSF(1),1)],[Clist(BSF(CityNum),2),Clist(BSF(1 ),2)],'ro-');title(['Counter:',int2str(p*Candidates),' The Min Distance:',num2str(BestL)]);hold off;pause(0.005);if get(stop,'value')==1break;endendtoc;BestShortcut=BSF;theMinDistance=BestL;set(stop,'style','pushbutton','string',…'close', 'callback','close(gcf)');figure(2);plot(ArrBestL,'r'); hold on;plot(ALong,'b');grid;title('搜索过程');legend('Best So Far','当前解');endfunction F=Fun(dislist,s) %#ok<DEFunNU>DistanV=0;n=size(s,2);for i=1:(n-1)DistanV=DistanV+dislist(s(i),s(i+1));endDistanV=DistanV+dislist(s(n),s(1));F=DistanV;end。