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2530. Maximal Score After Applying K Operations

Description

You are given a 0-indexed integer array nums and an integer k. You have a starting score of 0.

In one operation:

  1. choose an index i such that 0 <= i < nums.length,
  2. increase your score by nums[i], and
  3. replace nums[i] with ceil(nums[i] / 3).

Return the maximum possible score you can attain after applying exactly k operations.

The ceiling function ceil(val) is the least integer greater than or equal to val.

 

Example 1:

Input: nums = [10,10,10,10,10], k = 5
Output: 50
Explanation: Apply the operation to each array element exactly once. The final score is 10 + 10 + 10 + 10 + 10 = 50.

Example 2:

Input: nums = [1,10,3,3,3], k = 3
Output: 17
Explanation: You can do the following operations:
Operation 1: Select i = 1, so nums becomes [1,4,3,3,3]. Your score increases by 10.
Operation 2: Select i = 1, so nums becomes [1,2,3,3,3]. Your score increases by 4.
Operation 3: Select i = 2, so nums becomes [1,1,1,3,3]. Your score increases by 3.
The final score is 10 + 4 + 3 = 17.

 

Constraints:

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

Solutions

Solution 1: Priority Queue (Max Heap)

To maximize the sum of scores, we need to select the element with the maximum value at each step. Therefore, we can use a priority queue (max heap) to maintain the element with the maximum value.

At each step, we take out the element with the maximum value $v$ from the priority queue, add $v$ to the answer, and replace $v$ with $\lceil \frac{v}{3} \rceil$, and then add it to the priority queue. After repeating this process $k$ times, we return the answer.

The time complexity is $O(n + k \times \log n)$, and the space complexity is $O(n)$ or $O(1)$. Here, $n$ is the length of the array $nums$.

  • class Solution {
        public long maxKelements(int[] nums, int k) {
            PriorityQueue<Integer> pq = new PriorityQueue<>((a, b) -> b - a);
            for (int v : nums) {
                pq.offer(v);
            }
            long ans = 0;
            while (k-- > 0) {
                int v = pq.poll();
                ans += v;
                pq.offer((v + 2) / 3);
            }
            return ans;
        }
    }
    
  • class Solution {
    public:
        long long maxKelements(vector<int>& nums, int k) {
            priority_queue<int> pq(nums.begin(), nums.end());
            long long ans = 0;
            while (k--) {
                int v = pq.top();
                pq.pop();
                ans += v;
                pq.push((v + 2) / 3);
            }
            return ans;
        }
    };
    
  • class Solution:
        def maxKelements(self, nums: List[int], k: int) -> int:
            h = [-v for v in nums]
            heapify(h)
            ans = 0
            for _ in range(k):
                v = -heappop(h)
                ans += v
                heappush(h, -(ceil(v / 3)))
            return ans
    
    
  • func maxKelements(nums []int, k int) (ans int64) {
    	h := &hp{nums}
    	heap.Init(h)
    	for ; k > 0; k-- {
    		v := h.pop()
    		ans += int64(v)
    		h.push((v + 2) / 3)
    	}
    	return
    }
    
    type hp struct{ sort.IntSlice }
    
    func (h hp) Less(i, j int) bool { return h.IntSlice[i] > h.IntSlice[j] }
    func (h *hp) Push(v any)        { h.IntSlice = append(h.IntSlice, v.(int)) }
    func (h *hp) Pop() any {
    	a := h.IntSlice
    	v := a[len(a)-1]
    	h.IntSlice = a[:len(a)-1]
    	return v
    }
    func (h *hp) push(v int) { heap.Push(h, v) }
    func (h *hp) pop() int   { return heap.Pop(h).(int) }
    
  • function maxKelements(nums: number[], k: number): number {
        const pq = new MaxPriorityQueue();
        nums.forEach(num => pq.enqueue(num));
        let ans = 0;
        while (k > 0) {
            const v = pq.dequeue()!.element;
            ans += v;
            pq.enqueue(Math.floor((v + 2) / 3));
            k--;
        }
        return ans;
    }
    
    
  • use std::collections::BinaryHeap;
    
    impl Solution {
        pub fn max_kelements(nums: Vec<i32>, k: i32) -> i64 {
            let mut pq = BinaryHeap::from(nums);
            let mut ans = 0;
            let mut k = k;
            while k > 0 {
                if let Some(v) = pq.pop() {
                    ans += v as i64;
                    pq.push((v + 2) / 3);
                    k -= 1;
                }
            }
            ans
        }
    }
    
    

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