How to use a long matrix on matlab?

distMatrix = [0 25 4.2 4 23 6 23 1.4 9.5 2.3 27 26 28 2.5 8 6.3 22 5.4 22 31 20 1.8 25 7.8 5.7 28 9.8;
     25 0 24 23 12 21 13 25 17 24 6.8 18 16 23 18 20 10 25 11 5.7 5.4 25 18 18 7.6 4.3 17;
     4.2 24 0 0.2 20 4.7 17 3.1 4.8 3.9 25 30 39 2 4.3 2.6 20 8.4 20 29 18 2.7 23 4 3.1 25 4.9;
     4 23 0.2 0 20 4.8 17 2.7 4.9 3.5 25 30 39 1.6 4.4 2.8 20 7.7 20 29 18 2.3 23 4.1 3.2 25 5;
     23 12 20 20 0 20 24 24 16 23 9.1 30 28 23 17 21 1.9 24 1.7 17 7.7 25 6 16 9.1 11 16;
     6 21 4.7 4.8 20 0 18 5.1 5.2 3.9 22 38 37 3.4 3.2 1.6 17 5 21 26 15 5.5 21 3.7 1 23 5;
     23 13 17 17 24 18 0 22 12 21 19 18 17 19 14 17 23 22 23 7 18 22 30 14 0.4 17 13;
     1.4 25 3.1 2.7 24 5.1 22 0 9.7 0.5 26 27 29 1.5 7 5.4 21 4.7 25 30 19 0.8 24 7.6 4.8 27 9.2;
     9.5 17 4.8 4.9 16 5.2 12 9.7 0 8.2 19 35 33 6.4 1.9 4.6 14 9.5 14 23 12 9.7 17 1.1 3.8 19 0.5;
     2.3 24 3.9 3.5 23 3.9 21 0.5 8.2 0 25 27 40 2 6.3 4.6 20 4.7 25 29 18 1.3 24 6.8 4.1 26 8.1;
     27 6.8 25 25 9.1 22 19 26 19 25 0 25 23 25 20 22 7.5 27 7.9 12 10 27 15 19 12 2.4 19;
     26 18 30 30 30 38 18 27 35 27 25 0 2 28 36 38 28 29 28 12 23 27 36 36 18 22 35;
     28 16 39 39 28 37 17 29 33 40 23 2 0 30 35 37 27 31 27 11 22 29 35 35 17 21 34;
     2.5 23 2 1.6 23 3.4 19 1.5 6.4 2 25 28 30 0 5.8 4 20 6.1 24 29 18 0.7 23 5.3 3.5 25 6.3 ;
     8 18 4.3 4.4 17 3.2 14  7 1.9 6.3 20 36 35 5.8 0 2.7 15 7.4 16 24 13 7.8 18 0.9 2.3 21 1.8;
     6.3 20 2.6 2.8 21 1.6 17 5.4 4.6 4.6 22 38 37 4 2.7 0 17 5.7 18 26 15 4.7 20 3.5 0.4 23 4.4;
     22 10 20 20 1.9 17 23 21 14 20 7.5 28 27 20 15 17 0 31 1.2 16 6.1 22 7.8 15 7.6 9.8 14;
     5.4 25 8.4 7.7 24 5 22 4.7 9.5 4.7 27 29 31 6.1 7.4 5.7 31 0 24 31 20 5.4 29 7.9 1.7 27 9.5;
     22 11 20 20 1.7 21 23 25 14 25 7.9 28 27 24 16 18 1.2 24 0 16 6.5  25 7.3 15 7.9 11 14;
     31 5.7 29 29 17 26 7 30 23 29 12 12 11 29 24 26 16 31 16 0 11 31 23 23 7 10 23 ;
     20 5.4 18 18 7.7 15 18 19 12 18 10 23 22 18 13 15 6.1 20 6.5 11 0 20 14 13 2.3 7.6 12;
     1.8 25 2.7 2.3 25 5.5 22 0.8 9.7 1.3 27 27 29 0.7 7.8 4.7 22 5.4 25 3120 0 25 6 5.6 27 7;
     25 18 23 236 21 30 24 17 24 15 36 35 23 18 20 7.8 29 7.3 23 14 25 0 18 15 17 17;
     7.8 18 4 4.1 16 3.7 14 7.6 1.1 6.8 19 36 35 5.3 0.9 3.5 15 7.9 15 23 13 6 18 0 2.8 20 1.2;
     5.7 7.6 3.1 3.2 9.1 1 0.4 4.8 3.8 4.1 12 18 17 3.5 2.3 0.4 7.6 1.7 7.9 7 2.3 5.6 15 2.8 0 9.9 4.3;
     28 4.3 25 25 11 23 17 27 19 26 2.4 22 21 25 21 23 9.8 27 11 10 7.6 27 17 20 9.9 0 19;
     9.8 17 4.9 5 16 5 13 9.2 0.5 8.1 19 35 34 6.3 1.8 4.4 14 9.5 14 23 12 7 17 1.2 4.3 19 0
   ];

Error using vertcat
Dimensions of arrays being concatenated are not consistent.

populationSize = 100;  % Population size for GA
maxGenerations = 1000; % Number of generations for GA
initialTemperature = 100;  % Initial temperature for SA
coolingRate = 0.995;      % Cooling rate for SA
mutationRate = 2;    % Maximum number of iterations for SA

[bestTour, bestCost] = hybridTSP(distMatrix, populationSize, maxGenerations, initialTemperature, coolingRate, mutationRate);
disp('Best Tour:');
disp(bestTour);
disp(['Best Cost: ', num2str(bestCost)]);

function [bestTour, bestCost] = hybridTSP(distMatrix, populationSize, maxGenerations, initialTemperature, coolingRate, mutationRate)
    numCities = size(distMatrix, 1);
    
    % Generate initial tour using the nearest neighbor heuristic
    initialTour = nearestNeighbor(distMatrix);
    currentTour = initialTour;
    bestTour = initialTour;
    currentCost = calculateTourCost(currentTour, distMatrix);
    bestCost = currentCost;
    
    for generation = 1:maxGenerations
        temperature = initialTemperature / (1 + coolingRate * generation);
        
        % Apply Genetic Algorithm
        population = generatePopulation(populationSize, numCities);
        for i = 1:populationSize
            population(i, :) = mutate(population(i, :), mutationRate);
        end
        [population, costs] = evaluatePopulation(population, distMatrix);
        
        % Apply Simulated Annealing
        for i = 1:populationSize
            newTour = simulatedAnnealing(population(i, :), currentCost, temperature, distMatrix);
            newCost = calculateTourCost(newTour, distMatrix);
            
            if newCost < currentCost || rand() < exp((currentCost - newCost) / temperature)
                currentTour = newTour;
                currentCost = newCost;
                
                if newCost < bestCost
                    bestTour = currentTour;
                    bestCost = newCost;
                end
            end
        end
    end
end

function tour = nearestNeighbor(distMatrix)
    numCities = size(distMatrix, 1);
    tour = zeros(1, numCities);
    unvisited = 1:numCities;
    currentCity = randi(numCities);
    tour(1) = currentCity;
    unvisited(unvisited == currentCity) = [];
    
    for i = 2:numCities
        nearestCity = unvisited(1);
        minDistance = distMatrix(currentCity, nearestCity);
        
        for j = 2:length(unvisited)
            city = unvisited(j);
            distance = distMatrix(currentCity, city);
            if distance < minDistance
                nearestCity = city;
                minDistance = distance;
            end
        end
        
        tour(i) = nearestCity;
        currentCity = nearestCity;
        unvisited(unvisited == nearestCity) = [];
    end
end

function cost = calculateTourCost(tour, distMatrix)
    numCities = length(tour);
    cost = 0;
    for i = 1:numCities-1
        cost = cost + distMatrix(tour(i), tour(i+1));
    end
    cost = cost + distMatrix(tour(end), tour(1)); % Return to the starting city
end

function population = generatePopulation(populationSize, numCities)
    population = zeros(populationSize, numCities);
    for i = 1:populationSize
        population(i, :) = randperm(numCities);
    end
end

function mutatedTour = mutate(tour, mutationRate)
    numCities = length(tour);
    if rand() < mutationRate
        % Swap two random cities
        r1 = randi(numCities);
        r2 = randi(numCities);
        temp = tour(r1);
        tour(r1) = tour(r2);
        tour(r2) = temp;
    end
    mutatedTour = tour;
end

function [population, costs] = evaluatePopulation(population, distMatrix)
    populationSize = size(population, 1);
    costs = zeros(1, populationSize);
    for i = 1:populationSize
        costs(i) = calculateTourCost(population(i, :), distMatrix);
    end
    [~, idx] = sort(costs);
    population = population(idx, :);
    costs = costs(idx);
end

function newTour = simulatedAnnealing(tour, currentCost, temperature, distMatrix)
    numCities = length(tour);
    newTour = tour;
    
    % Perform 2-opt swap
    i = randi(numCities);
    j = randi(numCities);
    if i > j
        temp = i;
        i = j;
        j = temp;
    end
    
    while i < j
        temp = newTour(i);
        newTour(i) = newTour(j);
        newTour(j) = temp;
        i = i + 1;
        j = j - 1;
    end
    
    newCost = calculateTourCost(newTour, distMatrix);
    
    if newCost < currentCost || rand() < exp((currentCost - newCost) / temperature)
        currentCost = newCost;
    else
        % Revert the change
        while i < j
            temp = newTour(i);
            newTour(i) = newTour(j);
            newTour(j) = temp;
            i = i + 1;
            j = j - 1;
        end
    end
end

Hey everyone,

Please help me to fix this error. My algorithm is correct and it is running on small matrices. I have to solve the 27 by 27 matrix as provided here. Please help me to resolve the issue.

Thanks in advance!

Answer 1

[Dyuman Joshi]

The matrix is not 27x27. There are elements missing in the 22nd and 23rd row.

Check the data again.

[Amna Habib]

Thanks a lot @Dyuman Joshi. I have corrected this mistake. Now it is running