1052. Grumpy Bookstore Owner
Description
There is a bookstore owner that has a store open for n
minutes. You are given an integer array customers
of length n
where customers[i]
is the number of the customers that enter the store at the start of the ith
minute and all those customers leave after the end of that minute.
During certain minutes, the bookstore owner is grumpy. You are given a binary array grumpy where grumpy[i]
is 1
if the bookstore owner is grumpy during the ith
minute, and is 0
otherwise.
When the bookstore owner is grumpy, the customers entering during that minute are not satisfied. Otherwise, they are satisfied.
The bookstore owner knows a secret technique to remain not grumpy for minutes
consecutive minutes, but this technique can only be used once.
Return the maximum number of customers that can be satisfied throughout the day.
Example 1:
Input: customers = [1,0,1,2,1,1,7,5], grumpy = [0,1,0,1,0,1,0,1], minutes = 3
Output: 16
Explanation:
The bookstore owner keeps themselves not grumpy for the last 3 minutes.
The maximum number of customers that can be satisfied = 1 + 1 + 1 + 1 + 7 + 5 = 16.
Example 2:
Input: customers = [1], grumpy = [0], minutes = 1
Output: 1
Constraints:
n == customers.length == grumpy.length
1 <= minutes <= n <= 2 * 104
0 <= customers[i] <= 1000
grumpy[i]
is either0
or1
.
Solutions
Solution 1: Sliding Window
According to the problem description, we only need to count the number of customers when the boss is not angry $tot$, and add the maximum number of customers when the boss is angry within a sliding window of size minutes
$mx$.
We define a variable $cnt$ to record the number of customers when the boss is angry within the sliding window, the initial value is the number of customers when the boss is angry in the first minutes
. Then we traverse the array, each time we move the sliding window, we update the value of $cnt$, and at the same time update the value of $mx$.
Finally, return $tot + mx$.
The time complexity is $O(n)$, where $n$ is the length of the array customers
. The space complexity is $O(1)$.
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