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2542. Maximum Subsequence Score

Description

You are given two 0-indexed integer arrays nums1 and nums2 of equal length n and a positive integer k. You must choose a subsequence of indices from nums1 of length k.

For chosen indices i0, i1, ..., ik - 1, your score is defined as:

  • The sum of the selected elements from nums1 multiplied with the minimum of the selected elements from nums2.
  • It can defined simply as: (nums1[i0] + nums1[i1] +...+ nums1[ik - 1]) * min(nums2[i0] , nums2[i1], ... ,nums2[ik - 1]).

Return the maximum possible score.

A subsequence of indices of an array is a set that can be derived from the set {0, 1, ..., n-1} by deleting some or no elements.

 

Example 1:

Input: nums1 = [1,3,3,2], nums2 = [2,1,3,4], k = 3
Output: 12
Explanation: 
The four possible subsequence scores are:
- We choose the indices 0, 1, and 2 with score = (1+3+3) * min(2,1,3) = 7.
- We choose the indices 0, 1, and 3 with score = (1+3+2) * min(2,1,4) = 6. 
- We choose the indices 0, 2, and 3 with score = (1+3+2) * min(2,3,4) = 12. 
- We choose the indices 1, 2, and 3 with score = (3+3+2) * min(1,3,4) = 8.
Therefore, we return the max score, which is 12.

Example 2:

Input: nums1 = [4,2,3,1,1], nums2 = [7,5,10,9,6], k = 1
Output: 30
Explanation: 
Choosing index 2 is optimal: nums1[2] * nums2[2] = 3 * 10 = 30 is the maximum possible score.

 

Constraints:

  • n == nums1.length == nums2.length
  • 1 <= n <= 105
  • 0 <= nums1[i], nums2[j] <= 105
  • 1 <= k <= n

Solutions

Solution 1: Sorting + Priority Queue (Min Heap)

Sort nums2 and nums1 in descending order according to nums2, then traverse from front to back, maintaining a min heap. The heap stores elements from nums1, and the number of elements in the heap does not exceed $k$. At the same time, maintain a variable $s$ representing the sum of the elements in the heap, and continuously update the answer during the traversal process.

The time complexity is $O(n \times \log n)$, and the space complexity is $O(n)$. Here, $n$ is the length of the array nums1.

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class Solution:
    def maxScore(self, nums1: List[int], nums2: List[int], k: int) -> int:
        nums = sorted(zip(nums2, nums1), reverse=True)
        q = []
        ans = s = 0
        for a, b in nums:
            s += b
            heappush(q, b)
            if len(q) == k:
                ans = max(ans, s * a)
                s -= heappop(q)
        return ans
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class Solution {
    public long maxScore(int[] nums1, int[] nums2, int k) {
        int n = nums1.length;
        int[][] nums = new int[n][2];
        for (int i = 0; i < n; ++i) {
            nums[i] = new int[] {nums1[i], nums2[i]};
        }
        Arrays.sort(nums, (a, b) -> b[1] - a[1]);
        long ans = 0, s = 0;
        PriorityQueue<Integer> q = new PriorityQueue<>();
        for (int i = 0; i < n; ++i) {
            s += nums[i][0];
            q.offer(nums[i][0]);
            if (q.size() == k) {
                ans = Math.max(ans, s * nums[i][1]);
                s -= q.poll();
            }
        }
        return ans;
    }
}
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class Solution {
public:
    long long maxScore(vector<int>& nums1, vector<int>& nums2, int k) {
        int n = nums1.size();
        vector<pair<int, int>> nums(n);
        for (int i = 0; i < n; ++i) {
            nums[i] = {-nums2[i], nums1[i]};
        }
        sort(nums.begin(), nums.end());
        priority_queue<int, vector<int>, greater<int>> q;
        long long ans = 0, s = 0;
        for (auto& [a, b] : nums) {
            s += b;
            q.push(b);
            if (q.size() == k) {
                ans = max(ans, s * -a);
                s -= q.top();
                q.pop();
            }
        }
        return ans;
    }
};
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