【路径规划-TSP问题】基于禁忌搜索算法求解旅行商问题Matlab源码2 上传.zip

clc; clear; close all; %% Problem Definition model = CreateModel(); % Create TSP Model CostFunction=@(tour) TourLength(tour, model); % Cost Function ActionList=CreatePermActionList(model.n); % Action List nAction=numel(ActionList); % Number of Actions %% Tabu Search Parameters MaxIt=50; % Maximum Number of Iterations TL=round(0.5*nAction); % Tabu Length %% Initialization % Create Empty Individual Structure empty_individual.Position=[]; empty_individual.Cost=[]; % Create Initial Solution sol=empty_individual; sol.Position=randperm(model.n); sol.Cost=CostFunction(sol.Position); % Initialize Best Solution Ever Found BestSol=sol; % Array to Hold Best Costs BestCost=zeros(MaxIt,1); % Initialize Action Tabu Counters TC=zeros(nAction,1); %% Tabu Search Main Loop for it=1:MaxIt bestnewsol.Cost=inf; % Apply Actions for i=1:nAction if TC(i)==0 newsol.Position=DoAction(sol.Position,ActionList{i}); newsol.Cost=CostFunction(newsol.Position); newsol.ActionIndex=i; if newsol.Cost<=bestnewsol.Cost bestnewsol=newsol; end end end % Update Current Solution sol=bestnewsol; % Update Tabu List for i=1:nAction if i==bestnewsol.ActionIndex TC(i)=TL; % Add To Tabu List else TC(i)=max(TC(i)-1,0); % Reduce Tabu Counter end end % Update Best Solution Ever Found if sol.Cost<=BestSol.Cost BestSol=sol; end % Save Best Cost Ever Found BestCost(it)=BestSol.Cost; % Show Iteration Information disp(['Iteration ' num2str(it) ': Best Cost = ' num2str(BestCost(it))]); % Plot Best Solution figure(1); PlotSolution(BestSol, model); pause(0.01); % If Global Minimum is Reached if BestCost(it)==0 break; end end BestCost=BestCost(1:it); %% Results figure; plot(BestCost,'LineWidth',2); xlabel('Iteration'); ylabel('Best Cost'); grid on;