【LeetCode】826. Most Profit Assigning Work 解题报告(Python)

作者: 负雪明烛
id: fuxuemingzhu
个人博客: http://fuxuemingzhu.cn/


题目地址: https://leetcode.com/problems/most-profit-assigning-work/description/

题目描述:

We have jobs: difficulty[i] is the difficulty of the ith job, and profit[i] is the profit of the ith job.

Now we have some workers. worker[i] is the ability of the ith worker, which means that this worker can only complete a job with difficulty at most worker[i].

Every worker can be assigned at most one job, but one job can be completed multiple times.

For example, if 3 people attempt the same job that pays $1, then the total profit will be $3. If a worker cannot complete any job, his profit is $0.

What is the most profit we can make?

Example 1:

Input: difficulty = [2,4,6,8,10], profit = [10,20,30,40,50], worker = [4,5,6,7]
Output: 100 
Explanation: Workers are assigned jobs of difficulty [4,4,6,6] and they get profit of [20,20,30,30] seperately.

Notes:

  1. 1 <= difficulty.length = profit.length <= 10000
  2. 1 <= worker.length <= 10000
  3. difficulty[i], profit[i], worker[i] are in range [1, 10^5]

题目大意

有一堆工作,每个工作有对应的难度和收益,现在有几个工人需要干活,一个工人不能干几个活,但是一个活可以被多个工人多次的干。问这批工人能获得的最大收益。

解题方法

给的提示是双指针,其实我第一感觉是贪心的。事实上就是贪心。

贪心的策略是给每个工人计算在他的能力范围内,他能获得的最大收益,把这样的工作分配给他。

做的方法是先把困难程度和收益压缩排序,然后对工人排序,再对每个工人,通过从左到右的遍历确定其能获得收益最大值。由于工作和工人都已经排好序了,每次只需要从上次停止的位置继续即可,因此各自只需要遍历一次。

你可能会想到,每个工作的收益和其困难程度可能不是正相关的,可能存在某个工作难度小,但是收益反而很大,这种怎么处理呢?其实这也就是这个算法妙的地方,curMax并不是在每个工人查找其满足条件的工作时初始化的,而是在一开始就初始化了,这样一直保持的是所有的工作难度小于工人能力的工作中,能获得的收益最大值。

也就是说在查找满足条件的工作的时候,curMax有可能不更新,其保存的是目前为止的最大。res加的也就是在满足工人能力情况下的最大收益了。

时间复杂度是O(M+N),空间复杂度是O(MN)。

class Solution(object):
    def maxProfitAssignment(self, difficulty, profit, worker):
        """
        :type difficulty: List[int]
        :type profit: List[int]
        :type worker: List[int]
        :rtype: int
        """
        jobs = sorted([a, b] for a, b in zip(difficulty, profit))
        curMax, i = 0, 0
        res = 0
        for w in sorted(worker):
            while i < len(jobs) and w >= jobs[i][0]:
                curMax = max(curMax, jobs[i][1])
                i += 1
            res += curMax
        return res

参考资料:

https://leetcode.com/problems/most-profit-assigning-work/discuss/127031/C++JavaPython-Sort-and-Two-pointer

日期

2018 年 10 月 17 日 —— 今又重阳,战地黄花分外香

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