蚁群算法的示例代码(使用matlab)
时间: 2024-02-25 20:49:56 浏览: 19
以下是一个使用MATLAB实现蚁群算法的示例代码:
```matlab
% 蚁群算法参数设置
numAnts = 50; % 蚂蚁数量
numIterations = 100; % 迭代次数
alpha = 1; % 信息素重要程度因子
beta = 5; % 启发函数重要程度因子
rho = 0.5; % 信息素挥发因子
Q = 1; % 信息素增加强度因子
% 初始化问题和蚂蚁
problem = [1 3 5 2 4; 4 2 1 5 3]; % 问题矩阵
numCities = size(problem, 2); % 城市数量
pheromone = ones(numCities, numCities); % 信息素矩阵
bestTour = zeros(1, numCities); % 最佳路径
bestTourLength = Inf; % 最佳路径长度
% 迭代搜索
for iter = 1:numIterations
% 初始化蚂蚁位置和已访问城市
ants = randi([1 numCities], numAnts, 1);
visited = false(numAnts, numCities);
% 蚂蚁搜索路径
for k = 1:numCities-1
for i = 1:numAnts
currentCity = ants(i);
visited(i, currentCity) = true;
% 计算下一个城市的选择概率
unvisitedCities = find(~visited(i, :));
probabilities = (pheromone(currentCity, unvisitedCities).^alpha) .* (1./problem(currentCity, unvisitedCities).^beta);
probabilities = probabilities / sum(probabilities);
% 选择下一个城市
nextCity = randsample(unvisitedCities, 1, true, probabilities);
ants(i) = nextCity;
end
end
% 更新信息素
deltaPheromone = zeros(numCities, numCities);
for i = 1:numAnts
tour = [ants(i) ants(i)];
tourLength = 0;
for j = 1:numCities-1
currentCity = tour(j);
nextCity = tour(j+1);
tourLength = tourLength + problem(currentCity, nextCity);
end
if tourLength < bestTourLength
bestTour = tour;
bestTourLength = tourLength;
end
for j = 1:numCities-1
currentCity = tour(j);
nextCity = tour(j+1);
deltaPheromone(currentCity, nextCity) = deltaPheromone(currentCity, nextCity) + Q / tourLength;
end
end
pheromone = (1-rho) * pheromone + deltaPheromone;
end
% 输出最佳路径和最佳路径长度
disp('Best tour:');
disp(bestTour);
disp('Best tour length:');
disp(bestTourLength);
```
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