Leetcode 3568. Minimum Moves to Clean the Classroom

  • [Leetcode 3568. Minimum Moves to Clean the Classroom](#Leetcode 3568. Minimum Moves to Clean the Classroom)
    • [1. 解题思路](#1. 解题思路)
    • [2. 代码实现](#2. 代码实现)

1. 解题思路

这一题我的核心思路就是广度优先遍历遍历+剪枝。

显然,我们可以给出一个广度优先遍历来给出所有可能的走法直至无法继续或者捡完所有垃圾。

但是,上述情况事实上可能会无限循环下去,而且所有的走法也非常浪费,因此,我们需要对其进行剪枝,从而优化我们的计算。

而这里,我的剪枝思路就是:

  • 如果一个点曾经走过,则当他重新回到这个点的时候,他必须满足以下两个条件之一,否则这条路线必然不会是最优的,可以直接忽略:
    • 他在中间的过程中捡过了新的垃圾;
    • 他在中间的过程中补充了能量(即回来时的能量值大于之前来的时候的能量值)

由此,我们就能对上述问题进行解答了。

2. 代码实现

给出python代码实现如下:

python 复制代码
class Solution:
    def minMoves(self, classroom: List[str], energy: int) -> int:
        n, m = len(classroom), len(classroom[0])
        k, mapping, seen = 0, {}, {}
        for i in range(n):
            for j in range(m):
                if classroom[i][j] == "L":
                    mapping[(i, j)] = k
                    k += 1
                elif classroom[i][j] == "S":
                    start = (0, 0, -energy, i, j)
                    seen[(0, i, j)] = energy
        if k == 0:
            return 0

        q = [start]
        while q:
            step, status, e, i, j = heapq.heappop(q)
            status = -status
            e = -e
            if status == (2**k)-1:
                return step
            elif e <= 0:
                continue
            if i-1 >= 0 and classroom[i-1][j] != "X":
                new_status = status if classroom[i-1][j] != "L" else status | (1 << mapping[(i-1, j)])
                new_energy = e-1 if classroom[i-1][j] != "R" else energy
                if seen.get((new_status, i-1, j), -1) < new_energy:
                    heapq.heappush(q, (step+1, -new_status, -new_energy, i-1, j))
                    seen[(new_status, i-1, j)] = new_energy
            if i+1 < n and classroom[i+1][j] != "X":
                new_status = status if classroom[i+1][j] != "L" else status | (1 << mapping[(i+1, j)])
                new_energy = e-1 if classroom[i+1][j] != "R" else energy
                if seen.get((new_status, i+1, j), -1) < new_energy:
                    heapq.heappush(q, (step+1, -new_status, -new_energy, i+1, j))
                    seen[(new_status, i+1, j)] = new_energy
            if j-1 >= 0 and classroom[i][j-1] != "X":
                new_status = status if classroom[i][j-1] != "L" else status | (1 << mapping[(i, j-1)])
                new_energy = e-1 if classroom[i][j-1] != "R" else energy
                if seen.get((new_status, i, j-1), -1) < new_energy:
                    heapq.heappush(q, (step+1, -new_status, -new_energy, i, j-1))
                    seen[(new_status, i, j-1)] = new_energy
            if j+1 < m and classroom[i][j+1] != "X":
                new_status = status if classroom[i][j+1] != "L" else status | (1 << mapping[(i, j+1)])
                new_energy = e-1 if classroom[i][j+1] != "R" else energy
                if seen.get((new_status, i, j+1), -1) < new_energy:
                    heapq.heappush(q, (step+1, -new_status, -new_energy, i, j+1))
                    seen[(new_status, i, j+1)] = new_energy
        return -1

提交代码评测得到:耗时3097ms,占用内存58.28MB。

相关推荐
是阿建吖!3 天前
【递归、搜索与回溯算法】穷举、暴搜、深搜、回溯、剪枝
算法·bfs·剪枝
爱分享的飘哥5 天前
第六十一章:AI 模型的“视频加速术”:Wan视频扩散模型优化
人工智能·剪枝·tensorrt·量化·模型优化·视频扩散模型·cuda graph
Espresso Macchiato6 天前
Leetcode 3644. Maximum K to Sort a Permutation
leetcode medium·位操作·数组排序·leetcode 3644·leetcode周赛462
qiuyunoqy7 天前
蓝桥杯算法之搜索章 - 3
c++·算法·蓝桥杯·深度优先·dfs·剪枝
麦兜*9 天前
Spring Boot整合PyTorch Pruning工具链,模型瘦身手术
java·pytorch·spring boot·后端·spring cloud·ai编程·剪枝
Espresso Macchiato17 天前
Leetcode 3629. Minimum Jumps to Reach End via Prime Teleportation
bfs·广度优先遍历·leetcode medium·leetcode 3629·leetcode周赛460·质数求解·质因素分解
算法_小学生19 天前
决策树(Decision Tree)完整解析:原理 + 数学推导 + 剪枝 + 实战
算法·决策树·剪枝
hans汉斯24 天前
【建模与仿真】基于双流Mobile Vit与通道剪枝的工业过程故障诊断
java·c语言·人工智能·python·算法·机器学习·剪枝
tongxianchao1 个月前
LaCo: Large Language Model Pruning via Layer Collapse
人工智能·语言模型·剪枝
binnnngo1 个月前
Minmax 算法与 Alpha-Beta 剪枝小教学
算法·机器学习·剪枝