模拟退火算法及禁忌搜索算法的matlab源程序(共6页).doc

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1、精选优质文档-倾情为你奉上% 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;

2、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

3、+ . (CityPosition(:,2*ones(1,m) - CityPosition(:,2*ones(1,m).2);path=zeros(pn,m);for i=1:pn path(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=tau iter_num=1; m_num=1; while m_numm_max & iter_numiter_max fo

4、r 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-Len1R)=0) path(find(Len2-Len1R)=0),:)=path2(find(Len2-Len1R)=0),:); %

5、#ok Len1(find(Len2-Len1R)=0)=Len2(find(Len2-Len1R)=0); TempMinD,TempIndex=min(Len1); TracePath(N,:)=path(TempIndex,:); %#ok Distance(N)=TempMinD; %#ok N=N+1; else m_num=m_num+1; endend iter_num=iter_num+1; T=T*0.9;endMinD,Index=min(Distance);BestPath=TracePath(Index,:);%disp(MinD)%画出路线图figure(2);plo

6、t(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) 0 break; endendI=R(1);J=R(2);if IJ p2(1:I)=p1(1:I); p2(I+1:J)=p1(J:-1:I+1); p2(J+1:CityNum)=p1(J+1:CityNum);else p2(1:J-1)=p1(1:J-1); p2(J:I

7、+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;431

8、2 790;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:C

9、ityNum for j=1:CityNum dislist(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

10、BSF=S0;BestL=Inf;clf; figure(1);stop = uicontrol(style,toggle,string,stop,background,white);tic;p=1;StopL=80*CityNum;while pCityNum*(CityNum-1)/2 disp(候选解个数不大于n*(n-1)/2!); break; end ALong(p)=Fun(dislist,S0); i=1; A=zeros(Candidates,2); while i=Candidates M=CityNum*rand(1,2); M=ceil(M); if M(1)=M(2)

11、 A(i,1)=max(M(1),M(2); A(i,2)=min(M(1),M(2); if i=1 isa=0; else for j=1:i-1 if A(i,1)=A(j,1) & A(i,2)=A(j,2) isa=1; break; else isa=0; end end end if isa i=i+1; else end else end end BestCandidateNum=100;%保留前BestCandidateNum个最好候选解 BestCandidate=Inf*ones(BestCandidateNum,4); F=zeros(1,Candidates); fo

12、r i=1:Candidates CandidateNum(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=BestCandidateNum BestCandidate(i,2)=F(i); BestCandidate(i,1)=i; BestCandidate(i,3)=S0(A(i,1); BestCandidate(i,4)=S0(A(i,2); else for j=1:BestCandidateNum if F(i)BestCandidat

13、e(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; end end end end %对BestCandidate JL,Index=sort(BestCandidate(:,2); SBest=BestCandidate(Index,:); BestCandidate=SBest; if BestCandidate(1,2)BestL BestL=BestCandidate(1,2); S0=Candid

14、ateNum(BestCandidate(1,1),:); BSF=S0; for m=1:CityNum for n=1:CityNum if TabuList(m,n)=0 TabuList(m,n)=TabuList(m,n)-1; end end end TabuList(BestCandidate(1,3),BestCandidate(1,4)=TabuLength; else for i=1:BestCandidateNum if TabuList(BestCandidate(i,3),BestCandidate(i,4)=0 S0=CandidateNum(BestCandida

15、te(i,1),:); for m=1:CityNum for n=1:CityNum if TabuList(m,n)=0 TabuList(m,n)=TabuList(m,n)-1; end end end TabuList(BestCandidate(i,3),BestCandidate(i,4)=TabuLength; break; end end end p=p+1; ArrBestL(p)=BestL; %#ok for i=1:CityNum-1 plot(Clist(BSF(i),1),Clist(BSF(i+1),1),Clist(BSF(i),2),Clist(BSF(i+

16、1),2),bo-); hold on; end plot(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)=1 break; 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) %#okDistanV=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专心-专注-专业