Is Maximize Sum After At Most K Digit Rearrangements easy or hard?

It is a medium problem. The rearrangement logic is straightforward once you see that each number's gain is independent. The difficulty lies in recognizing the greedy choice and proving that picking the largest positive gains is optimal.

Maximize Sum After At Most K Digit Rearrangements Python solution?

In Python, convert each number to a string, sort its digits in reverse order with sorted(s, reverse=True), and compute the gain as the new integer minus the original. Filter positive gains, sort them with reverse=True, and return the original sum plus the sum of the first k gains.

What is the best approach for Maximize Sum After At Most K Digit Rearrangements?

The best approach is greedy. Compute the gain from sorting each number's digits in descending order, keep only the positive gains, sort them, and add the top k to the original sum. It runs in O(n log n) plus digit sorting time.

What data structure is used in Maximize Sum After At Most K Digit Rearrangements?

The greedy solution uses an array or list to store gains and relies on sorting. The DP solution uses a one-dimensional array of size k+1 as a knapsack table. No hash map or tree is required.

What is the time complexity of Maximize Sum After At Most K Digit Rearrangements?

The greedy solution runs in O(n * d log d + n log n) time, where n is the array length and d is the maximum number of digits per number. The DP solution runs in O(n * k) time. Space for the greedy is O(n).

Is Maximize Sum After At Most K Digit Rearrangements asked at Google, Amazon, or Meta?

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Description Solution Video 21:07

4093. Maximize Sum After At Most K Digit Rearrangements

Q: How to solve Maximize Sum After At Most K Digit Rearrangements in O(n log n)?

Sort each number's digits descending to get its best value and compute the gain against the original. Collect all positive gains, sort them in descending order, and add the first k to the original sum. The sort of gains is the O(n log n) step.

Medium50.9% acceptance

You are given an integer array nums of length n and an integer k.

In one operation, you may choose any element of nums and rearrange its decimal digits in any order to form a new integer.

Return the maximum possible sum of the array after performing at most k operations.

Example 1:

Input: nums = [123,45], k = 1

Output: 366

Explanation:

We choose nums[0] = 123 and rearrange its digits to form 321.
The array becomes [321, 45]. Thus, the total sum is 321 + 45 = 366.

Example 2:

Input: nums = [102,90,14], k = 2

Output: 341

Explanation:

We choose nums[0] = 102 and rearrange its digits to form 210.
We choose nums[2] = 14 and rearrange its digits to form 41.
The array becomes [210, 90, 41]. Thus, the total sum is 210 + 90 + 41 = 341.

Constraints:

1 <= n == nums.length <= 10⁵
1 <= nums[i] <= 10⁹
1 <= k <= n

21:07

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1class Solution:
2    def maximizeSum(self, nums: list[int], k: int) -> int:
3        

Starter codePython 3Spaces: 4

Examples

Case 1Case 2

Input

[123,45]
1

Input

[102,90,14]
2

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