1856. Maximum Subarray Min-Product
Description
The min-product of an array is equal to the minimum value in the array multiplied by the array's sum.
- For example, the array
[3,2,5]
(minimum value is2
) has a min-product of2 * (3+2+5) = 2 * 10 = 20
.
Given an array of integers nums
, return the maximum min-product of any non-empty subarray of nums
. Since the answer may be large, return it modulo 109 + 7
.
Note that the min-product should be maximized before performing the modulo operation. Testcases are generated such that the maximum min-product without modulo will fit in a 64-bit signed integer.
A subarray is a contiguous part of an array.
Example 1:
Input: nums = [1,2,3,2] Output: 14 Explanation: The maximum min-product is achieved with the subarray [2,3,2] (minimum value is 2). 2 * (2+3+2) = 2 * 7 = 14.
Example 2:
Input: nums = [2,3,3,1,2] Output: 18 Explanation: The maximum min-product is achieved with the subarray [3,3] (minimum value is 3). 3 * (3+3) = 3 * 6 = 18.
Example 3:
Input: nums = [3,1,5,6,4,2] Output: 60 Explanation: The maximum min-product is achieved with the subarray [5,6,4] (minimum value is 4). 4 * (5+6+4) = 4 * 15 = 60.
Constraints:
1 <= nums.length <= 105
1 <= nums[i] <= 107
Solutions
Solution 1: Monotonic Stack + Prefix Sum
We can enumerate each element $nums[i]$ as the minimum value of the subarray, and find the left and right boundaries $left[i]$ and $right[i]$ of the subarray. Where $left[i]$ represents the first position strictly less than $nums[i]$ on the left side of $i$, and $right[i]$ represents the first position less than or equal to $nums[i]$ on the right side of $i$.
To conveniently calculate the sum of the subarray, we can preprocess the prefix sum array $s$, where $s[i]$ represents the sum of the first $i$ elements of $nums$.
Then the minimum product with $nums[i]$ as the minimum value of the subarray is $nums[i] \times (s[right[i]] - s[left[i] + 1])$. We can enumerate each element $nums[i]$, find the minimum product with $nums[i]$ as the minimum value of the subarray, and then take the maximum value.
The time complexity is $O(n)$, and the space complexity is $O(n)$. Where $n$ is the length of the array $nums$.
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