LeetCode in Kotlin
1760. Minimum Limit of Balls in a Bag
Medium
You are given an integer array nums where the ith bag contains nums[i] balls. You are also given an integer maxOperations.
You can perform the following operation at most maxOperations times:
- Take any bag of balls and divide it into two new bags with a positive number of balls.
- For example, a bag of
5balls can become two new bags of1and4balls, or two new bags of2and3balls.
- For example, a bag of
Your penalty is the maximum number of balls in a bag. You want to minimize your penalty after the operations.
Return the minimum possible penalty after performing the operations.
Example 1:
Input: nums = [9], maxOperations = 2
Output: 3
Explanation:
-
Divide the bag with 9 balls into two bags of sizes 6 and 3. [9] -> [6,3].
-
Divide the bag with 6 balls into two bags of sizes 3 and 3. [6,3] -> [3,3,3]. The bag with the most number of balls has 3 balls, so your penalty is 3 and you should return 3.
Example 2:
Input: nums = [2,4,8,2], maxOperations = 4
Output: 2
Explanation:
-
Divide the bag with 8 balls into two bags of sizes 4 and 4. [2,4,8,2] -> [2,4,4,4,2].
-
Divide the bag with 4 balls into two bags of sizes 2 and 2. [2,4,4,4,2] -> [2,2,2,4,4,2].
-
Divide the bag with 4 balls into two bags of sizes 2 and 2. [2,2,2,4,4,2] -> [2,2,2,2,2,4,2].
-
Divide the bag with 4 balls into two bags of sizes 2 and 2. [2,2,2,2,2,4,2] -> [2,2,2,2,2,2,2,2]. The bag with the most number of balls has 2 balls, so your penalty is 2 an you should return 2.
Example 3:
Input: nums = [7,17], maxOperations = 2
Output: 7
Constraints:
1 <= nums.length <= 1051 <= maxOperations, nums[i] <= 109
Solution
class Solution {
fun minimumSize(nums: IntArray, maxOperations: Int): Int {
var left = 1
var right = 1000000000
while (left < right) {
val mid = left + (right - left) / 2
if (operations(nums, mid) > maxOperations) {
left = mid + 1
} else {
right = mid
}
}
return left
}
private fun operations(nums: IntArray, mid: Int): Int {
var operations = 0
for (num in nums) {
operations += (num - 1) / mid
}
return operations
}
}