用python写一段蚁群算法实例

好的，以下是用python实现基本的蚁群算法的示例代码：

import random

# 蚂蚁类
class Ant:
    def __init__(self, start, end, graph):
        self.current_node = start
        self.end_node = end
        self.graph = graph
        self.path = [start]
        self.distance = 0.0

    # 蚂蚁走一步
    def move(self, alpha, beta, pheromone):
        next_node = self.select_next(alpha, beta, pheromone)
        self.path.append(next_node)
        self.distance += self.graph[self.current_node][next_node]
        self.current_node = next_node

    # 选择下一个节点
    def select_next(self, alpha, beta, pheromone):
        # 如果当前节点是终点，直接返回
        if self.current_node == self.end_node:
            return self.end_node

        next_node = None
        # 计算每个节点的概率
        probabilities = {}
        denominator = 0.0
        for node in range(len(self.graph)):
            if node not in self.path:
                numerator = (pheromone[self.current_node][node] ** alpha) * \
                    ((1.0 / self.graph[self.current_node][node]) ** beta)
                probabilities[node] = numerator
                denominator += numerator

        # 根据概率选择下一个节点
        if denominator == 0.0:
            next_node = random.choice(list(set(range(len(self.graph))) - set(self.path)))
        else:
            probabilities = {node: prob / denominator for node, prob in probabilities.items()}
            probability_sum = 0.0
            target_probability = random.random()
            for node, prob in probabilities.items():
                probability_sum += prob
                if probability_sum >= target_probability:
                    next_node = node
                    break

        return next_node

# 蚁群算法函数
def ant_colony_algorithm(graph, start, end, ant_count=10, alpha=1.0, beta=2.0, evaporation=0.5, pheromone_deposit=1.0,
                         max_iterations=50):
    best_distance = float('inf')
    best_path = None
    pheromone = [[1.0 for _ in range(len(graph))] for _ in range(len(graph))]

    # 循环迭代
    for iteration in range(max_iterations):
        # 初始化蚂蚁
        ants = [Ant(start, end, graph) for _ in range(ant_count)]

        # 蚁群行动
        for ant in ants:
            while ant.current_node != ant.end_node:
                ant.move(alpha, beta, pheromone)
            if ant.distance < best_distance:
                best_distance = ant.distance
                best_path = ant.path

        # 更新信息素
        for i, row in enumerate(pheromone):
            for j, col in enumerate(row):
                pheromone[i][j] *= (1.0 - evaporation)
                for ant in ants:
                    if j == ant.path[i + 1]:
                        pheromone[i][j] += (pheromone_deposit / ant.distance)

    return best_path, best_distance

# 示例
graph = [[0, 3, 4, 5], [3, 0, 2, 3], [4, 2, 0, 1], [5, 3, 1, 0]]
start = 0
end = 3
path, distance = ant_colony_algorithm(graph, start, end)
print('最短路径: ', path)
print('最短距离: ', distance)

该示例代码实现了一个对一个简单的四节点图求解最短路径的蚁群算法。在实际应用时需要针对具体问题进行适当的参数调整和算法优化。