VRP.zip_vrp_vrp matlab_zip

clc; clear; close all; global NFE; NFE=0; %% Problem Definition model=SelectModel(); % Select Model of the Problem model.eta=0.1; CostFunction=@(q) MyCost(q,model); % Cost Function %% SA Parameters MaxIt=1200; % Maximum Number of Iterations MaxIt2=80; % Maximum Number of Inner Iterations T0=100; % Initial Temperature alpha=0.99; % Temperature Damping Rate %% Initialization % Create Initial Solution x.Position=CreateRandomSolution(model); [x.Cost x.Sol]=CostFunction(x.Position); % Update Best Solution Ever Found BestSol=x; % Array to Hold Best Cost Values BestCost=zeros(MaxIt,1); % Array to Hold NFEs nfe=zeros(MaxIt,1); % Set Initial Temperature T=T0; %% SA Main Loop for it=1:MaxIt for it2=1:MaxIt2 % Create Neighbor xnew.Position=CreateNeighbor(x.Position); [xnew.Cost xnew.Sol]=CostFunction(xnew.Position); if xnew.Cost<=x.Cost % xnew is better, so it is accepted x=xnew; else % xnew is not better, so it is accepted conditionally delta=xnew.Cost-x.Cost; p=exp(-delta/T); if rand<=p x=xnew; end end % Update Best Solution if x.Cost<=BestSol.Cost BestSol=x; end end % Store Best Cost BestCost(it)=BestSol.Cost; % Store NFE nfe(it)=NFE; % Display Iteration Information if BestSol.Sol.IsFeasible FLAG=' *'; else FLAG=''; end disp(['Iteration ' num2str(it) ': Best Cost = ' num2str(BestCost(it)) FLAG]); % Reduce Temperature T=alpha*T; % Plot Solution figure(1); PlotSolution(BestSol.Sol,model); end %% Results figure; plot(nfe,BestCost,'LineWidth',2); xlabel('NFE'); ylabel('Best Cost');