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

% 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

Answer 1

[ProblemSolver]

@Amna Habib --

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

[Amna Habib]

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]

@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.