Description
There is a group of n
members, and a list of various crimes they could commit. The ith
crime generates a profit[i]
and requires group[i]
members to participate in it. If a member participates in one crime, that member can't participate in another crime.
Let's call a profitable scheme any subset of these crimes that generates at least minProfit
profit, and the total number of members participating in that subset of crimes is at most n
.
Return the number of schemes that can be chosen. Since the answer may be very large, return it modulo 109 + 7
.
Example 1:
Input: n = 5, minProfit = 3, group = [2,2], profit = [2,3] Output: 2 Explanation: To make a profit of at least 3, the group could either commit crimes 0 and 1, or just crime 1. In total, there are 2 schemes.
Example 2:
Input: n = 10, minProfit = 5, group = [2,3,5], profit = [6,7,8] Output: 7 Explanation: To make a profit of at least 5, the group could commit any crimes, as long as they commit one. There are 7 possible schemes: (0), (1), (2), (0,1), (0,2), (1,2), and (0,1,2).
Constraints:
1 <= n <= 100
0 <= minProfit <= 100
1 <= group.length <= 100
1 <= group[i] <= 100
profit.length == group.length
0 <= profit[i] <= 100
Solution
Python3
class Solution:
def profitableSchemes(self, n: int, minProfit: int, group: List[int], profit: List[int]) -> int:
N = len(group)
M = 10 ** 9 + 7
@cache
def go(index, people, currProfit):
if people == 0 or index == N:
return currProfit >= minProfit
# skip
res = go(index + 1, people, currProfit)
if people - group[index] >= 0:
res += go(index + 1, people - group[index], min(currProfit + profit[index], minProfit))
return res % M
return go(0, n, 0)