Maximize the Minimum Powered City | Hard Made Easy | Leetcode 2528 | Codehurdle скачать в хорошем качестве

Maximize the Minimum Powered City | Hard Made Easy | Leetcode 2528 | Codehurdle

In this video, we solve LeetCode 2528: Maximize the Minimum Powered City, a challenging problem that combines Binary Search on Answer, Greedy strategy, and Sliding Window/Difference Array techniques to optimize power distribution across a city. 📌 In this video, you’ll learn: How to identify "Maximize the Minimum" patterns that signal Binary Search. The Greedy logic for placing additional power stations to provide maximum coverage. Using a Sliding Window or Difference Array to manage range sums efficiently. How to validate a potential "minimum power" value within the search space. Full Time & Space complexity analysis for large-scale constraints. This problem is excellent for mastering optimization over ranges and improving your ability to combine multiple algorithmic patterns—essential skills for top-tier technical interviews and competitive programming. 👉 Problem Link: https://leetcode.com/problems/maximiz... Practice More Problems on CodeHurdle: https://www.codehurdle.com Connect with CodeHurdle: 🌐 Website: https://www.codehurdle.com 📸 Instagram:   / codehurdle.official   📺 YouTube:    / @codehurdle   🔗 LinkedIn:   / codehurdle   #LeetCode #MaximizeTheMinimumPoweredCity #BinarySearch #Greedy #SlidingWindow #DSA #CompetitiveProgramming #LeetCodeSolution #CodeHurdle #InterviewPrep #HardMadeEasy