SA:利用SA算法解决TSP(数据是14个虚拟城市的横纵坐标)问题——Jason niu
%SA:利用SA算法解决TSP(数据是14个虚拟城市的横纵坐标)问题——Jason niu X = [16.4700 96.1000 16.4700 94.4400 20.0900 92.5400 22.3900 93.3700 25.2300 97.2400 22.0000 96.0500 20.4700 97.0200 17.2000 96.2900 16.3000 97.3800 14.0500 98.1200 16.5300 97.3800 21.5200 95.5900 19.4100 97.1300 20.0900 92.5500]; D = Distance(X); N = size(D,1); T0 = 1e10; Tend = 1e-30; L = 2; q = 0.9; Time = ceil(double(solve([num2str(T0) '*(0.9)^x = ',num2str(Tend)]))); count = 0; Obj = zeros(Time,1); track = zeros(Time,N); S1 = randperm(N); DrawPath(S1,X) title('利用自定义函数绘制TSP问题的初始路径(随机产生)—Jason niu') disp('初始种群中的一个随机值:') OutputPath(S1); Rlength = PathLength(D,S1); disp(['总距离:',num2str(Rlength)]); while T0 > Tend count = count + 1; temp = zeros(L,N+1); S2 = NewAnswer(S1); [S1,R] = Metropolis(S1,S2,D,T0); if count == 1 || R < Obj(count-1) Obj(count) = R; else Obj(count) = Obj(count-1); end track(count,:) = S1; T0 = q * T0; end figure plot(1:count,Obj) xlabel('迭代次数') ylabel('距离') title('SA:显示SA算法对TSP问题的优化过程(适应度函数)—Jason niu') DrawPath(track(end,:),X) title('SA:利用SA对TSP问题优化,绘制出利用SA算法优化后的最优路径图—Jason niu') %% IX. 输出最优解的路线和总距离 disp('最优解:') S = track(end,:); p = OutputPath(S); disp(['总距离:',num2str(PathLength(D,S))]);
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