帮我写一段matlab基于排序的蚁群算法解决tsp问题的代码

好的，以下是基于排序的蚁群算法解决 TSP 问题的 MATLAB 代码：

% TSP 问题的距离矩阵
distance = [0, 30, 84, 56, 70;
            30, 0, 65, 40, 72;
            84, 65, 0, 10, 45;
            56, 40, 10, 0, 50;
            70, 72, 45, 50, 0];

% 蚂蚁数量
numAnts = 50;

% 蚂蚁的初始位置
antPositions = randi([1, size(distance, 1)], numAnts, 1);

% 各个城市之间的信息素
pheromone = ones(size(distance));

% 最佳路径和最短距离的初始值
bestPath = [];
bestDistance = Inf;

% 迭代次数
numIterations = 100;

% 重复迭代过程
for iter = 1:numIterations
    
    % 重置蚂蚁的位置
    antPositions = randi([1, size(distance, 1)], numAnts, 1);
    
    % 每只蚂蚁移动一次
    for i = 1:numAnts
        
        % 记录已访问的城市
        visited = zeros(size(distance, 1), 1);
        
        % 记录访问过的路径
        path = zeros(size(distance, 1), 1);
        
        % 起始城市
        currentCity = antPositions(i);
        visited(currentCity) = 1;
        path(1) = currentCity;
        
        % 蚂蚁访问所有城市
        for j = 2:size(distance, 1)
            
            % 计算可行的下一个城市
            feasibleCities = find(~visited);
            probabilities = pheromone(currentCity, feasibleCities) ./ distance(currentCity, feasibleCities);
            probabilities = probabilities / sum(probabilities);
            nextCity = randsample(feasibleCities, 1, true, probabilities);
            
            % 更新已访问的城市和访问过的路径
            visited(nextCity) = 1;
            path(j) = nextCity;
            
            % 更新当前城市
            currentCity = nextCity;
        end
        
        % 计算当前路径的距离
        pathDistance = 0;
        for j = 1:size(distance, 1)-1
            pathDistance = pathDistance + distance(path(j), path(j+1));
        end
        pathDistance = pathDistance + distance(path(size(distance, 1)), path(1));
        
        % 更新最佳路径和最短距离
        if pathDistance < bestDistance
            bestPath = path;
            bestDistance = pathDistance;
        end
        
    end
    
    % 更新信息素
    deltaPheromone = zeros(size(distance));
    for i = 1:numAnts
        for j = 1:size(distance, 1)-1
            deltaPheromone(bestPath(j), bestPath(j+1)) = deltaPheromone(bestPath(j), bestPath(j+1)) + 1/bestDistance;
        end
        deltaPheromone(bestPath(size(distance, 1)), bestPath(1)) = deltaPheromone(bestPath(size(distance, 1)), bestPath(1)) + 1/bestDistance;
    end
    pheromone = (1-0.1) * pheromone + deltaPheromone;
    
end

% 输出结果
disp('最佳路径：');
disp(bestPath);
disp('最短距离：');
disp(bestDistance);

注意，这段代码只是一个简单的示例，实际使用时需要根据具体问题进行修改和优化。