You are given a 0-indexed array nums
comprising of n
non-negative integers.
In one operation, you must:
- Choose an integer
i
such that1 <= i < n
andnums[i] > 0
. - Decrease
nums[i]
by 1. - Increase
nums[i - 1]
by 1.
Return the minimum possible value of the maximum integer of nums
after performing any number of operations.
Example 1:
Input: nums = [3,7,1,6] Output: 5 Explanation: One set of optimal operations is as follows: 1. Choose i = 1, and nums becomes [4,6,1,6]. 2. Choose i = 3, and nums becomes [4,6,2,5]. 3. Choose i = 1, and nums becomes [5,5,2,5]. The maximum integer of nums is 5. It can be shown that the maximum number cannot be less than 5. Therefore, we return 5.
Example 2:
Input: nums = [10,1] Output: 10 Explanation: It is optimal to leave nums as is, and since 10 is the maximum value, we return 10.
Constraints:
n == nums.length
2 <= n <= 105
0 <= nums[i] <= 109
Related Topics:
Array, Binary Search, Dynamic Programming, Greedy, Prefix Sum
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// OJ: https://leetcode.com/problems/minimize-maximum-of-array
// Author: github.com/lzl124631x
// Time: O(NlogN)
// Space: O(1)
class Solution {
public:
int minimizeArrayValue(vector<int>& A) {
int L = 0, R = *max_element(begin(A), end(A));
auto valid = [&](long long mx) {
long long d = 0;
for (long long n : A) {
n += d;
if (n > mx) return false;
d = n - mx;
}
return true;
};
while (L <= R) {
int M = (L + R) / 2;
if (valid(M)) R = M - 1;
else L = M + 1;
}
return L;
}
};
Since the value can only flow forward (left), for A[0..i]
, assume its prefix sum is sum[i]
, the best we can do is to distribute this sum[i]
evenly into these i+1
elements. So, the maximum is ceil(sum[i] / (i+1))
.
We compute from left to right, and return the maximum of ceil(sum[i] / (i+1))
as the answer.
// OJ: https://leetcode.com/problems/minimize-maximum-of-array
// Author: github.com/lzl124631x
// Time: O(N)
// Space: O(1)
class Solution {
public:
int minimizeArrayValue(vector<int>& A) {
long long N = A.size(), ans = 0, sum = 0;
for (int i = 0; i < N; ++i) {
sum += A[i];
ans = max(ans, (sum + i) / (i + 1));
}
return ans;
}
};