LeetCode in Kotlin

1962. Remove Stones to Minimize the Total

Medium

You are given a 0-indexed integer array piles, where piles[i] represents the number of stones in the ith pile, and an integer k. You should apply the following operation exactly k times:

• Choose any piles[i] and remove floor(piles[i] / 2) stones from it.

Notice that you can apply the operation on the same pile more than once.

Return the minimum possible total number of stones remaining after applying the k operations.

floor(x) is the greatest integer that is smaller than or equal to x (i.e., rounds x down).

Example 1:

Input: piles = [5,4,9], k = 2

Output: 12

Explanation: Steps of a possible scenario are:

• Apply the operation on pile 2. The resulting piles are [5,4,5].

• Apply the operation on pile 0. The resulting piles are [3,4,5].

The total number of stones in [3,4,5] is 12.

Example 2:

Input: piles = [4,3,6,7], k = 3

Output: 12

Explanation: Steps of a possible scenario are:

• Apply the operation on pile 2. The resulting piles are [4,3,3,7].

• Apply the operation on pile 3. The resulting piles are [4,3,3,4].

• Apply the operation on pile 0. The resulting piles are [2,3,3,4].

The total number of stones in [2,3,3,4] is 12.

Constraints:

• 1 <= piles.length <= 105
• 1 <= piles[i] <= 104
• 1 <= k <= 105

Solution

import java.util.Collections
import java.util.PriorityQueue

@Suppress("NAME_SHADOWING")
class Solution {
    fun minStoneSum(piles: IntArray, k: Int): Int {
        var k = k
        val descendingQueue = PriorityQueue(Collections.reverseOrder<Int>())
        var sum = 0
        var newValue: Int
        var currentValue: Int
        var half: Int
        for (stones in piles) {
            sum += stones
            descendingQueue.offer(stones)
        }
        while (k > 0) {
            currentValue = descendingQueue.poll()
            half = currentValue / 2
            newValue = currentValue - half
            descendingQueue.offer(newValue)
            sum -= half
            k--
        }
        return sum
    }
}

This site is open source. Improve this page.