鱼群算法tsp 的matlab代码

鱼群算法（Fish School Search）是一种基于鱼群行为的启发式优化算法，用于解决旅行商问题（TSP）。下面是一个简单的鱼群算法TSP的Matlab代码示例：

% 鱼群算法TSP的Matlab代码示例

% 初始化参数
numFish = 50; % 鱼群数量
numIter = 100; % 迭代次数
alpha = 0.6; % 鱼的移动步长因子
beta = 0.08; % 鱼的视野范围因子
delta = 0.97; % 鱼的步长衰减因子

% 初始化城市坐标
cities = [0, 0; 1, 1; 2, 2; 3, 3; 4, 4];

% 计算城市之间的距离矩阵
numCities = size(cities, 1);
distMatrix = zeros(numCities, numCities);
for i = 1:numCities
    for j = 1:numCities
        distMatrix(i, j) = norm(cities(i, :) - cities(j, :));
    end
end

% 初始化鱼群位置和最优路径
fishPos = zeros(numFish, numCities);
fishBestPos = zeros(numFish, numCities);
fishBestDist = zeros(numFish, 1);

% 初始化全局最优路径和距离
globalBestPos = zeros(1, numCities);
globalBestDist = Inf;

% 迭代优化
for iter = 1:numIter
    % 更新鱼群位置
    for i = 1:numFish
        % 计算鱼的移动步长
        stepSize = alpha * delta^(iter-1);
        
        % 计算鱼的视野范围
        viewRange = beta * delta^(iter-1);
        
        % 在视野范围内选择最优路径
        neighbors = find(distMatrix(i, :) <= viewRange);
        [~, idx] = min(fishBestDist(neighbors));
        bestNeighbor = neighbors(idx);
        
        % 更新鱼的位置
        fishPos(i, :) = fishPos(i, :) + stepSize * (fishBestPos(bestNeighbor, :) - fishPos(i, :));
        
        % 计算当前路径长度
        dist = 0;
        for j = 1:numCities-1
            dist = dist + distMatrix(fishPos(i, j), fishPos(i, j+1));
        end
        dist = dist + distMatrix(fishPos(i, numCities), fishPos(i, 1));
        
        % 更新最优路径和距离
        if dist < fishBestDist(i)
            fishBestPos(i, :) = fishPos(i, :);
            fishBestDist(i) = dist;
        end
        
        % 更新全局最优路径和距离
        if dist < globalBestDist
            globalBestPos = fishPos(i, :);
            globalBestDist = dist;
        end
    end
end

% 输出结果
disp('最优路径：');
disp(globalBestPos);
disp('最优距离：');
disp(globalBestDist);

希望这个代码示例能够帮助到你。如果有任何问题，请随时提问。