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Plotting an algorithm with distance matrix as input and all iteration results as output

2 vues (au cours des 30 derniers jours)
% Example distance matrix (replace it with your own)
distanceMatrix = [
0 10 15 20;
10 0 35 25;
15 35 0 30;
20 25 30 0
];
% Set algorithm parameters
maxIterations = 1000;
tabuSize = 10;
% Run Tabu Search
[bestTour, bestDistance, iterationResults] = tabuSearchTSP(distanceMatrix, maxIterations, tabuSize);
Error using solution>tabuSearchTSP
Too many output arguments.
% Display the best tour and its distance
disp('Best Tour:');
disp(bestTour);
disp('Best Distance:');
disp(bestDistance);
% Display the output of each iteration
disp('Iteration Results:');
for i = 1:maxIterations
disp(['Iteration ', num2str(iterationResults(i).Iteration)]);
disp('Best Tour:');
disp(iterationResults(i).BestTour);
disp('Best Distance:');
disp(iterationResults(i).BestDistance);
disp('-----------------');
end
function [bestTour, bestDistance] = tabuSearchTSP(distanceMatrix, maxIterations, tabuSize)
% Initialize variables
n = size(distanceMatrix, 1); % Number of cities
tabuList = zeros(n, tabuSize); % Tabu list to store recently visited solutions
currentTour = randperm(n); % Random initial solution
bestTour = currentTour;
bestDistance = calculateTourDistance(currentTour, distanceMatrix);
iteration = 1;
while iteration <= maxIterations
candidateList = generateCandidateList(currentTour, tabuList);
[bestCandidate, bestCandidateDistance] = evaluateCandidates(candidateList, distanceMatrix);
if bestCandidateDistance < bestDistance
bestTour = bestCandidate;
bestDistance = bestCandidateDistance;
end
currentTour = bestCandidate;
tabuList = updateTabuList(tabuList, currentTour);
iteration = iteration + 1;
end
end
function distance = calculateTourDistance(tour, distanceMatrix)
n = length(tour);
distance = 0;
for i = 1:n-1
distance = distance + distanceMatrix(tour(i), tour(i+1));
end
distance = distance + distanceMatrix(tour(n), tour(1)); % Return to the starting city
end
function candidateList = generateCandidateList(currentTour, tabuList)
candidateList = [];
n = length(currentTour);
for i = 1:n-1
for j = i+1:n
candidate = currentTour;
candidate(i) = currentTour(j);
candidate(j) = currentTour(i);
if ~isTabu(candidate, tabuList)
candidateList = [candidateList; candidate];
end
end
end
end
function isTabu = isTabu(candidate, tabuList)
[n, tabuSize] = size(tabuList);
isTabu = false;
for i = 1:tabuSize
if isequal(candidate, tabuList(:, i))
isTabu = true;
break;
end
end
end
function [bestCandidate, bestCandidateDistance] = evaluateCandidates(candidateList, distanceMatrix)
numCandidates = size(candidateList, 1);
bestCandidateDistance = Inf;
for i = 1:numCandidates
candidate = candidateList(i, :);
candidateDistance = calculateTourDistance(candidate, distanceMatrix);
if candidateDistance < bestCandidateDistance
bestCandidate = candidate;
bestCandidateDistance = candidateDistance;
end
end
end
function tabuList = updateTabuList(tabuList, candidate)
[n, tabuSize] = size(tabuList);
tabuList = [candidate' tabuList(:, 1:tabuSize-1)];
end
Hi,
The output is not shown here as I need result for each iteration. But if I want only final best solution, it gives output.
Please modify it or help to fix the error. Thanks

Réponses (1)

ProblemSolver
ProblemSolver le 10 Juil 2023
Please find the change. You need to add an output argument that will store the best tour and distance for each iteration.
% Example distance matrix (replace it with your own)
distanceMatrix = [
0 10 15 20;
10 0 35 25;
15 35 0 30;
20 25 30 0
];
% Set algorithm parameters
maxIterations = 10;
tabuSize = 10;
% Run Tabu Search
[bestTour, bestDistance, iterationResults] = tabuSearchTSP(distanceMatrix, maxIterations, tabuSize);
% Display the best tour and its distance
disp('Best Tour:');
Best Tour:
disp(bestTour);
3 4 2 1
disp('Best Distance:');
Best Distance:
disp(bestDistance);
80
% Display the output of each iteration
disp('Iteration Results:');
Iteration Results:
for i = 1:maxIterations
disp(['Iteration ', num2str(iterationResults(i).Iteration)]);
disp('Best Tour:');
disp(iterationResults(i).BestTour);
disp('Best Distance:');
disp(iterationResults(i).BestDistance);
disp('-----------------');
end
Iteration 1
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
Iteration 2
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
Iteration 3
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
Iteration 4
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
Iteration 5
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
Iteration 6
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
Iteration 7
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
Iteration 8
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
Iteration 9
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
Iteration 10
Best Tour:
3 4 2 1
Best Distance:
80
-----------------
function [bestTour, bestDistance, iterationResults] = tabuSearchTSP(distanceMatrix, maxIterations, tabuSize)
% Initialize variables
n = size(distanceMatrix, 1); % Number of cities
tabuList = zeros(n, tabuSize); % Tabu list to store recently visited solutions
currentTour = randperm(n); % Random initial solution
bestTour = currentTour;
bestDistance = calculateTourDistance(currentTour, distanceMatrix);
% Initialize iteration results
iterationResults = struct('Iteration', {}, 'BestTour', {}, 'BestDistance', {});
iteration = 1;
while iteration <= maxIterations
candidateList = generateCandidateList(currentTour, tabuList);
[bestCandidate, bestCandidateDistance] = evaluateCandidates(candidateList, distanceMatrix);
if bestCandidateDistance < bestDistance
bestTour = bestCandidate;
bestDistance = bestCandidateDistance;
end
currentTour = bestCandidate;
tabuList = updateTabuList(tabuList, currentTour);
% Store iteration results
iterationResults(iteration).Iteration = iteration;
iterationResults(iteration).BestTour = bestTour;
iterationResults(iteration).BestDistance = bestDistance;
iteration = iteration + 1;
end
end
function distance = calculateTourDistance(tour, distanceMatrix)
n = length(tour);
distance = 0;
for i = 1:n-1
distance = distance + distanceMatrix(tour(i), tour(i+1));
end
distance = distance + distanceMatrix(tour(n), tour(1)); % Return to the starting city
end
function candidateList = generateCandidateList(currentTour, tabuList)
candidateList = [];
n = length(currentTour);
for i = 1:n-1
for j = i+1:n
candidate = currentTour;
candidate(i) = currentTour(j);
candidate(j) = currentTour(i);
if ~isTabu(candidate, tabuList)
candidateList = [candidateList; candidate];
end
end
end
end
function isTabu = isTabu(candidate, tabuList)
[n, tabuSize] = size(tabuList);
isTabu = false;
for i = 1:tabuSize
if isequal(candidate, tabuList(:, i))
isTabu = true;
break;
end
end
end
function [bestCandidate, bestCandidateDistance] = evaluateCandidates(candidateList, distanceMatrix)
numCandidates = size(candidateList, 1);
bestCandidateDistance = Inf;
for i = 1:numCandidates
candidate = candidateList(i, :);
candidateDistance = calculateTourDistance(candidate, distanceMatrix);
if candidateDistance < bestCandidateDistance
bestCandidate = candidate;
bestCandidateDistance = candidateDistance;
end
end
end
function tabuList = updateTabuList(tabuList, candidate)
[n, tabuSize] = size(tabuList);
tabuList = [candidate' tabuList(:, 1:tabuSize-1)];
end
  2 commentaires
Amna Habib
Amna Habib le 10 Juil 2023
OK Got it!
Thanks a lot @ProblemSolver
Now I am shock that all iterations result are same. it means there is some issue in matlb code?
do you have any idea that when portion of code has some mistake? i could not find any error yet
ProblemSolver
ProblemSolver le 11 Juil 2023
@Amna Habib. You need to explain me what are you looking for by performing this algorithm? as in theoritically what is expected? and other details to really see what part of the code is generating that.

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