给一个蚁群算法的python代码
时间: 2023-06-10 08:02:40 浏览: 48
当然,我可以向您提供一个蚁群算法的Python代码示例:
```
import random
# 初始化信息素矩阵
def init_pheromone(N, alpha, beta):
pheromone = [ [1.0/N for j in range(N)] for i in range(N) ]
return pheromone, alpha, beta
# 计算路径长度
def cal_path_length(distance, path):
path_length = 0
for i in range(len(path)-1):
path_length += distance[path[i]][path[i+1]]
return path_length
# 权重概率
def cal_prob(weight, alpha, beta, pheromone):
n = len(weight)
prob_list = [0 for i in range(n)]
total_prob = 0
for i in range(n):
if weight[i] != 0:
prob = pow(pheromone[i], alpha) * pow(1.0/weight[i], beta)
prob_list[i] = prob
total_prob += prob
for i in range(n):
if weight[i] != 0:
prob_list[i] /= total_prob
return prob_list
# 轮盘赌法(选择下一个节点)
def select_next_node(prob_list):
rand = random.random()
accumulate_prob = 0
for i in range(len(prob_list)):
accumulate_prob += prob_list[i]
if accumulate_prob >= rand:
return i
# 更新信息素矩阵
def update_pheromone(pheromone, path, ant_num, Q):
delta_pheromone = [ [0.0 for j in range(len(pheromone))] for i in range(len(pheromone))]
path_length = cal_path_length(distance, path)
for i in range(len(path)-1):
start, end = path[i], path[i+1]
delta_pheromone[start][end] = Q/path_length/ant_num
delta_pheromone[end][start] = delta_pheromone[start][end]
for i in range(len(pheromone)):
for j in range(len(pheromone)):
pheromone[i][j] = (1-0.5)*pheromone[i][j]+delta_pheromone[i][j]
# 蚁群算法主程序
def ant_algorithm(distance, ant_num, alpha, beta, Q, max_iter):
best_path = []
best_length = float("inf")
pheromone, alpha, beta = init_pheromone(len(distance), alpha, beta)
for iter_ in range(max_iter):
ant_paths = []
for ant_id in range(ant_num):
cur_node = random.randint(0, len(distance)-1)
visited_nodes = [cur_node]
unvisited_nodes = set(range(len(distance)))
unvisited_nodes.remove(cur_node)
while unvisited_nodes:
weight = list(distance[cur_node][i] for i in unvisited_nodes)
prob_list = cal_prob(weight, alpha, beta, pheromone[cur_node])
next_node = select_next_node(prob_list)
visited_nodes.append(next_node)
unvisited_nodes.remove(next_node)
cur_node = next_node
path_len = cal_path_length(distance, visited_nodes)
ant_paths.append([visited_nodes, path_len])
if path_len < best_length:
best_path = visited_nodes
best_length = path_len
update_pheromone(pheromone, best_path, ant_num, Q)
return best_path, best_length
```
如果您对代码有任何问题或需要做出修改,请告诉我。