人工蜂群算法求解0-1背包问题python代码
时间: 2023-11-06 12:18:11 浏览: 49
以下是使用Python实现人工蜂群算法求解0-1背包问题的代码:
```python
import random
# 背包容量
capacity = 50
# 物品重量
weights = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
# 物品价值
values = [20, 30, 40, 50, 60, 70, 80, 90, 100, 110]
# 蜜蜂数量
bee_num = 100
# 最大迭代次数
max_iter = 1000
# 最大空负荷次数
max_idle = 100
# 飞行距离
flight_distance = 10
# 最大不改进次数
max_no_improve = 10
# 初始化蜜蜂
def init_bees():
bees = []
for i in range(bee_num):
bee = []
for j in range(len(weights)):
bee.append(random.randint(0, 1))
bees.append(bee)
return bees
# 计算蜜蜂的适应度
def fitness(bee):
weight = 0
value = 0
for i in range(len(bee)):
if bee[i] == 1:
weight += weights[i]
value += values[i]
if weight > capacity:
value = 0
return value
# 计算蜜蜂的局部搜索结果
def local_search(bee):
for i in range(len(bee)):
if random.random() < 0.5:
bee[i] = 1 - bee[i]
return bee
# 计算蜜蜂的全局搜索结果
def global_search(bee, bees):
max_fitness = 0
max_bee = bee
for i in range(len(bees)):
fitness_val = fitness(bees[i])
if fitness_val > max_fitness:
max_fitness = fitness_val
max_bee = bees[i]
for i in range(len(bee)):
if random.random() < 0.5:
bee[i] = max_bee[i]
return bee
# 计算蜜蜂的飞行结果
def flight(bee, bees):
neighbor_fitness = []
for i in range(len(bees)):
if bee != bees[i]:
neighbor_fitness.append((i, fitness(bees[i])))
neighbor_fitness.sort(key=lambda x: x[1], reverse=True)
max_fitness = neighbor_fitness[0][1]
max_bee_index = neighbor_fitness[0][0]
for i in range(len(bees[max_bee_index])):
if random.random() < 0.5:
bee[i] = bees[max_bee_index][i]
return bee
# 人工蜂群算法
def artificial_bee_colony():
bees = init_bees()
iter_count = 0
idle_count = 0
no_improve_count = 0
global_best_fitness = 0
global_best_bee = []
while iter_count < max_iter and idle_count < max_idle and no_improve_count < max_no_improve:
for i in range(len(bees)):
if random.random() < 0.3:
new_bee = local_search(bees[i])
elif random.random() < 0.6:
new_bee = global_search(bees[i], bees)
else:
new_bee = flight(bees[i], bees)
if fitness(new_bee) > fitness(bees[i]):
bees[i] = new_bee
if fitness(new_bee) > global_best_fitness:
global_best_fitness = fitness(new_bee)
global_best_bee = new_bee
no_improve_count = 0
else:
no_improve_count += 1
idle_count += 1
if no_improve_count == max_no_improve:
idle_count = 0
iter_count += 1
return (global_best_bee, global_best_fitness)
# 测试算法
result = artificial_bee_colony()
print("最优解:", result[0])
print("最优值:", result[1])
```
在这个代码中,我们使用了Python语言来实现人工蜂群算法求解0-1背包问题。首先,我们定义了背包容量、物品重量、物品价值、蜜蜂数量、最大迭代次数、最大空负荷次数、飞行距离和最大不改进次数等参数。然后,我们定义了初始化蜜蜂、计算蜜蜂的适应度、计算蜜蜂的局部搜索结果、计算蜜蜂的全局搜索结果和计算蜜蜂的飞行结果等函数。最后,我们定义了人工蜂群算法函数,用于求解0-1背包问题。在测试算法时,我们输出了最优解和最优值。