LeetCode 2462. Total Cost to Hire K Workers Solution in Java, C++, Python & More | Explanation + Code

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2462. Total Cost to Hire K Workers

Description

You are given a 0-indexed integer array costs where costs[i] is the cost of hiring the ith worker.

You are also given two integers k and candidates. We want to hire exactly k workers according to the following rules:

  • You will run k sessions and hire exactly one worker in each session.
  • In each hiring session, choose the worker with the lowest cost from either the first candidates workers or the last candidates workers. Break the tie by the smallest index.
    • For example, if costs = [3,2,7,7,1,2] and candidates = 2, then in the first hiring session, we will choose the 4th worker because they have the lowest cost [3,2,7,7,1,2].
    • In the second hiring session, we will choose 1st worker because they have the same lowest cost as 4th worker but they have the smallest index [3,2,7,7,2]. Please note that the indexing may be changed in the process.
  • If there are fewer than candidates workers remaining, choose the worker with the lowest cost among them. Break the tie by the smallest index.
  • A worker can only be chosen once.

Return the total cost to hire exactly k workers.

 

Example 1:

Input: costs = [17,12,10,2,7,2,11,20,8], k = 3, candidates = 4
Output: 11
Explanation: We hire 3 workers in total. The total cost is initially 0.
- In the first hiring round we choose the worker from [17,12,10,2,7,2,11,20,8]. The lowest cost is 2, and we break the tie by the smallest index, which is 3. The total cost = 0 + 2 = 2.
- In the second hiring round we choose the worker from [17,12,10,7,2,11,20,8]. The lowest cost is 2 (index 4). The total cost = 2 + 2 = 4.
- In the third hiring round we choose the worker from [17,12,10,7,11,20,8]. The lowest cost is 7 (index 3). The total cost = 4 + 7 = 11. Notice that the worker with index 3 was common in the first and last four workers.
The total hiring cost is 11.

Example 2:

Input: costs = [1,2,4,1], k = 3, candidates = 3
Output: 4
Explanation: We hire 3 workers in total. The total cost is initially 0.
- In the first hiring round we choose the worker from [1,2,4,1]. The lowest cost is 1, and we break the tie by the smallest index, which is 0. The total cost = 0 + 1 = 1. Notice that workers with index 1 and 2 are common in the first and last 3 workers.
- In the second hiring round we choose the worker from [2,4,1]. The lowest cost is 1 (index 2). The total cost = 1 + 1 = 2.
- In the third hiring round there are less than three candidates. We choose the worker from the remaining workers [2,4]. The lowest cost is 2 (index 0). The total cost = 2 + 2 = 4.
The total hiring cost is 4.

 

Constraints:

  • 1 <= costs.length <= 105
  • 1 <= costs[i] <= 105
  • 1 <= k, candidates <= costs.length

Solutions

Solution 1: Priority Queue (Min Heap)

First, we check if candidates × 2 is greater than or equal to n. If it is, we directly return the sum of the costs of the first k smallest workers.

Otherwise, we use a min heap pq to maintain the costs of the first candidates workers and the last candidates workers.

We first add the costs and corresponding indices of the first candidates workers to the min heap pq, and then add the costs and corresponding indices of the last candidates workers to the min heap pq. We use two pointers l and r to point to the indices of the front and back candidates, initially l = candidates, r = n - candidates - 1.

Then we perform k iterations, each time taking the worker with the smallest cost from the min heap pq and adding its cost to the answer. If l > r, it means that all the front and back candidates have been selected, and we skip directly. Otherwise, if the index of the current worker is less than l, it means it is a worker from the front, we add the cost and index of the l-th worker to the min heap pq, and then increment l; otherwise, we add the cost and index of the r-th worker to the min heap pq, and then decrement r.

After the loop ends, we return the answer.

The time complexity is O(n × log n), and the space complexity is O(n). Where n is the length of the array costs.

PythonJavaC++GoTypeScript
class Solution: def totalCost(self, costs: List[int], k: int, candidates: int) -> int: n = len(costs) if candidates * 2 >= n: return sum(sorted(costs)[:k]) pq = [] for i, c in enumerate(costs[:candidates]): heappush(pq, (c, i)) for i in range(n - candidates, n): heappush(pq, (costs[i], i)) heapify(pq) l, r = candidates, n - candidates - 1 ans = 0 for _ in range(k): c, i = heappop(pq) ans += c if l > r: continue if i < l: heappush(pq, (costs[l], l)) l += 1 else: heappush(pq, (costs[r], r)) r -= 1 return ans(code-box)

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