SA: Using SA algorithm to solve TSP (data is the horizontal ordinate of 14 virtual cities) problem--jason Niu

%SA: Using SA algorithm to solve TSP (data is a horizontal ordinate of 14 virtual cities)--jason niu X = [16.4700 96.1000 16.4700 94.4400 20.0900 92.5400 22.39      00 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 = Distan  CE (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 (' The initial path to draw a TSP problem using a custom function (randomly generated)-jason niu ') disp (' a random value in the initial population: ') OutputPath (S1); Rlength = Pathlength (D,S1);         DISP ([' Total Distance: ', 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; Endfigureplot (1:count,obj) xlabel (' Iteration count ') ylabel (' Distance ') title (' SA: shows the SA algorithm's optimization process for TSP (fitness function)-jason niu ') DrawPath ( Track (end,:), X) title (' SA: using SA to optimize the TSP problem, draw the optimal path graph-jason niu ') percent IX using SA algorithm optimization. The route and total distance of the output optimal solution disp (' Optimal solution: ') S = Track (end,:);p = OutputPath (S);d ISP ([' Total Distance: ', Num2str (Pathlength (d,s)]));

SA: Using SA algorithm to solve TSP (data is the horizontal ordinate of 14 virtual cities) problem--jason Niu