Скачать или смотреть Maximum Performance of a Team | Greedy + Heap JavaScript Solution Explained | LeetCode Hard

In this video, we solve the “Maximum Performance of a Team” problem using JavaScript, one of the most asked LeetCode Hard problems.
We combine Greedy strategy and Min Heap (Priority Queue) to achieve an O(n log n) efficient solution.

Problem Explanation:
We are given n engineers with speed and efficiency.
We must select at most k engineers to maximize:
Performance = (Sum of Speeds) * (Minimum Efficiency)

We sort engineers by efficiency (descending) and use a Min Heap to track the top k speeds while updating the maximum performance at each step.

Example:

Input: n = 6, speed = [2,10,3,1,5,8], efficiency = [5,4,3,9,7,2], k = 2 Output: 60

Concepts Covered:

Greedy Algorithm

Heap / Priority Queue

Sorting Optimization

Time Complexity: O(n log n)

JavaScript DSA Problem Solving

Perfect for DSA practice, coding interviews, and LeetCode preparation!



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