Bin packing问题指在给定的若干个物品中选出一定数量进行装箱，并使得所选的物品的体积和不超过每个箱子的容积，并且所选的箱子数量最少。这是一个NP-hard问题，暴力解法时间复杂度为指数级别，因此一般使用近似算法进行求解。

以下是一个基于深度优先搜索（DFS）的暴力解法示例：

class Bin:
    def __init__(self, capacity):
        self.capacity = capacity
        self.remaining_capacity = capacity

    def pack(self, item_size):
        if item_size > self.remaining_capacity:
            return False
        self.remaining_capacity -= item_size
        return True

class BinPacking:
    def __init__(self, bin_capacity, item_sizes):
        self.bin_capacity = bin_capacity
        self.item_sizes = item_sizes
        self.best_solution = None

    def brute_force(self):
        current_solution = []
        self._dfs(current_solution)

    def _dfs(self, current_solution):
        if self.best_solution is not None and len(current_solution) >= len(self.best_solution):
            return

        if len(self.item_sizes) == 0:
            self.best_solution = current_solution[:]
            return

        item_size = self.item_sizes.pop(0)

        # try adding the item to existing bins
        for i, bin in enumerate(current_solution):
            if bin.pack(item_size):
                self._dfs(current_solution)
                bin.remaining_capacity += item_size
                if bin.remaining_capacity == self.bin_capacity:
                    current_solution.pop(i)
                else:
                    bin.remaining_capacity -= item_size

        # try adding the item to a new bin
        new_bin = Bin(self.bin_capacity)
        if new_bin.pack(item_size):
            current_solution.append(new_bin)
            self._dfs(current_solution)
            current_solution.pop()

        self.item_sizes.insert(0, item_size)

详细说明：首先定义Bin类来表示一个箱子，包含容积和剩余容积的属性以及pack方法，用于将物