Minimum Array Sum | Detailed for Beginners | Contest Problem | Leetcode 3366 | codestorywithMIK
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This is the 104th Video of our Playlist "Dynamic Programming : Popular Interview Problems" by codestorywithMIK
In this video we will try to solve a good practice DP Problem : Minimum Array Sum | Detailed for Beginners | Leetcode 3366 | codestorywithMIK
This is today's Leetcode Contest 3rd Problem - 24th Nov,2024
This is a good problem for an interview and hence I felt that I should make a video on this one. I have also explained why Greedy fails in the approach.
I will explain the intuition so easily that you will never forget and start seeing this as cakewalk EASYYY.
We will do live coding after explanation and see if we are able to pass all the test cases.
Also, please note that my Github solution link below contains both C++ as well as JAVA code.
Problem Name : Minimum Array Sum | Detailed for Beginners | Leetcode 3366 | codestorywithMIK
Company Tags : will update
My solutions on Github(C++ & JAVA) - https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/DP/1-D DP/Minimum Array Sum.cpp
Leetcode Link : https://leetcode.com/problems/minimum-array-sum
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Summary :
The approach aims to minimize the sum of an array after applying up to two types of operations a limited number of times:
Operation 1: Reduces an element by half (rounded up).
Operation 2: Reduces an element by a fixed amount, k.
The problem is solved using recursion with memoization, ensuring optimal performance by avoiding redundant computations. The main steps are:
Recursive Function (solve):
At each index i, the algorithm evaluates all possible ways to reduce the element:
Apply Operation 1 if allowed.
Apply Operation 2 if the element is greater than or equal to k and allowed.
Apply both operations in different orders to explore combinations.
Skip operations for the current element and move to the next.
Memoization:
A 3D memo array stores results for each (i, op1, op2) state to avoid redundant computations.
Base Case:
If all elements are processed (i == n), return 0 as no further operations are possible.
Result Calculation:
For each possible operation, compute the resulting value and recursively solve for the remaining array, keeping track of the minimum sum.
✨ Timelines✨
00:00 - Introduction
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