826. Most Profit Assigning Work

Problem Link

Description

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You have n jobs and m workers. You are given three arrays: difficulty, profit, and worker where:

• difficulty[i] and profit[i] are the difficulty and the profit of the ith job, and
• worker[j] is the ability of jth worker (i.e., the jth worker can only complete a job with difficulty at most worker[j]).

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

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

Return the maximum profit we can achieve after assigning the workers to the jobs.

 

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 a profit of [20,20,30,30] separately.

Example 2:

Input: difficulty = [85,47,57], profit = [24,66,99], worker = [40,25,25]
Output: 0

 

Constraints:

• n == difficulty.length
• n == profit.length
• m == worker.length
• 1 <= n, m <= 104
• 1 <= difficulty[i], profit[i], worker[i] <= 105

Solution

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Python3

class Solution:
    def maxProfitAssignment(self, difficulty: List[int], profit: List[int], worker: List[int]) -> int:
        N, M = len(difficulty), len(worker)
        sortedDifficulty = sorted(range(N), key = lambda i : difficulty[i])
        res = index = maxProfit = 0
 
        for ability in sorted(worker):
            while index < N and ability >= difficulty[sortedDifficulty[index]]:
                maxProfit = max(maxProfit, profit[sortedDifficulty[index]])
                index += 1
            
            res += maxProfit
 
        return res