这个代码并不完整，请帮我在matlab上用蚁群算法写出解决多旅行商问题的完整代码

当涉及到多旅行商问题时，使用蚁群算法可以得到一个相对较好的解决方案。以下是MATLAB实现多旅行商问题的蚁群算法的代码示例：

% 定义问题
num_cities = 10;    % 城市数量
num_ants = 20;      % 蚂蚁数量
alpha = 1;          % Alpha参数
beta = 5;           % Beta参数
evaporation_rate = 0.5; % 挥发率
pheromone_init = 0.1; % 初始信息素浓度
num_iterations = 200; % 迭代次数

% 生成城市坐标
cities = 10*rand(num_cities,2);

% 计算城市之间的距离
distances = pdist2(cities,cities);

% 初始化信息素浓度矩阵
pheromone = pheromone_init*ones(num_cities,num_cities);

% 初始化最优路径及长度
best_path = [];
best_path_length = Inf;

% 开始迭代
for iteration = 1:num_iterations
    % 初始化每个蚂蚁的起点和访问城市的顺序
    ant_tour = zeros(num_ants,num_cities);
    for ant = 1:num_ants
        ant_tour(ant,1) = randi([1 num_cities]);
    end
    
    % 每只蚂蚁开始访问其他城市
    for city = 2:num_cities
        for ant = 1:num_ants
            % 计算蚂蚁ant在当前城市的选择概率
            current_city = ant_tour(ant,city-1);
            unvisited_cities = setdiff(1:num_cities,ant_tour(ant,1:city-1));
            probabilities = zeros(size(unvisited_cities));
            for i = 1:length(unvisited_cities)
                next_city = unvisited_cities(i);
                probabilities(i) = (pheromone(current_city,next_city)^alpha)*(1/distances(current_city,next_city)^beta);
            end
            probabilities = probabilities/sum(probabilities);
            
            % 轮盘赌选择下一个城市
            cumulative_probabilities = cumsum(probabilities);
            r = rand;
            for i = 1:length(cumulative_probabilities)
                if r < cumulative_probabilities(i)
                    next_city = unvisited_cities(i);
                    break;
                end
            end
            
            % 将下一个城市添加到蚂蚁的路径中
            ant_tour(ant,city) = next_city;
        end
    end
    
    % 更新信息素浓度矩阵
    delta_pheromone = zeros(num_cities,num_cities);
    for ant = 1:num_ants
        for city = 1:num_cities-1
            current_city = ant_tour(ant,city);
            next_city = ant_tour(ant,city+1);
            delta_pheromone(current_city,next_city) = delta_pheromone(current_city,next_city) + 1/distances(current_city,next_city);
            delta_pheromone(next_city,current_city) = delta_pheromone(current_city,next_city);
        end