Maximum Strength of K Disjoint Subarrays | Recursion | Memoization | Leetcode 3077 | Contest 388
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This is the 89th Video of our Playlist "Dynamic Programming : Popular Interview Problems".
In this video we will try to solve a very good DP problem : Maximum Strength of K Disjoint Subarrays | Recursion | Memoization | Clean and Simple | Leetcode 3077
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Problem Name : Maximum Strength of K Disjoint Subarrays | Recursion | Memoization | Clean and Simple | Leetcode 3077
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My solutions on Github(C++ & JAVA) : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/DP/Maximum%20Strength%20of%20K%20Disjoint%20Subarrays.cpp
Leetcode Link : https://leetcode.com/problems/maximum-strength-of-k-disjoint-subarrays/description/
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Approach Summary :
The maximumStrength function initializes necessary variables, including the size of the array n and a 3D vector dp used for dynamic programming memoization. It then calls the solve function to recursively explore and calculate the maximum strength, considering two cases: taking the current element or skipping it. The solve function uses memoization to optimize repeated calculations and implements two cases: taking or not taking the current element. The strength calculation involves considering whether the current subarray starts a new one or continues from the previous. The goal is to maximize the overall strength of the selected subarrays while adhering to the specified rules. The final result, representing the maximum strength, is returned by the maximumStrength function.
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✨ Timelines✨
00:00 - Introduction
00:55 - Problem Explanation
07:03 - Intuition Building
07:47 - Tree Diagram
22:50 - Story Points
32:53 - Coding it up & Time and Space Complexity
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