基于退火的三维装箱问题python代码

基于退火算法求解三维装箱问题的Python代码可以如下：

import random
import math

# 定义装箱向量（Box）类
class Box:
    def __init__(self, x, y, z, id):
        self.x = x
        self.y = y
        self.z = z
        self.id = id

# 生成n个待装箱的物品列表
def generate_items(n):
    items = []
    for i in range(n):
        x = random.randint(1, 100)
        y = random.randint(1, 100)
        z = random.randint(1, 100)
        item = Box(x, y, z, i)
        items.append(item)
    return items

# 计算方案的体积
def get_volume(boxes):
    volume = 0
    for box in boxes:
        volume += box.x * box.y * box.z
    return volume

# 计算温度
def get_temperature(iteration):
    return 200 / iteration

# 判断是否接受新方案
def accept_new_solution(delta_E, T):
    if delta_E < 0:
        return True
    else:
        p = math.exp(-delta_E / T)
        if random.random() < p:
            return True
        else:
            return False

# 利用退火算法求解三维装箱问题
def solve_packing(items, T0=200, alpha=0.95, stopping_temperature=10 ** -10, max_iteration=10 ** 4):
    current_solution = []
    for item in items:
        current_solution.append(item)
    best_solution = current_solution
    current_volume = get_volume(current_solution)
    best_volume = current_volume
    T = T0
    iteration = 0
    while T > stopping_temperature and iteration < max_iteration:
        i = random.randint(0, len(items) - 1)
        j = random.randint(0, len(items) - 1)
        while j == i:
            j = random.randint(0, len(items) - 1)
        proposal_solution = current_solution.copy()
        proposal_solution[i], proposal_solution[j] = proposal_solution[j], proposal_solution[i]
        proposal_volume = get_volume(proposal_solution)
        delta_E = proposal_volume - current_volume
        if accept_new_solution(delta_E, T):
            current_solution = proposal_solution
            current_volume = proposal_volume
            if current_volume < best_volume:
                best_solution = current_solution
                best_volume = current_volume
        T = alpha * T
        iteration += 1
    return best_volume, best_solution

# 测试代码
if __name__ == '__main__':
    items = generate_items(10)   # 生成10个待装箱的物品
    volume, boxes = solve_packing(items)   # 求解
    print("体积：", volume)
    for box in boxes:
        print("物品{}：x={}，y={}，z={}".format(box.id, box.x, box.y, box.z))

在代码中，首先定义了表示装箱向量的类Box。generate_items函数用于生成n个待装箱的物品，在本例中生成了10个，每个物品的边长随机生成。get_volume函数用于计算方案的体积。get_temperature函数用于计算当前温度，其值会随着迭代次数不断降低。accept_new_solution函数用于根据温度随机判断是否接受新方案。solve_packing函数用于利用退火算法求解三维装箱问题，其中T0为初始温度，alpha为降温系数，stopping_temperature为停止温度，max_iteration为最大迭代次数。最后，测试代码生成10个物品，求解，输出最优解的体积及装箱方案的详细信息。