Formatted question description: https://leetcode.ca/all/1753.html

1753. Maximum Score From Removing Stones

Medium

Description

You are playing a solitaire game with three piles of stones of sizes a, b, and c respectively. Each turn you choose two different non-empty piles, take one stone from each, and add 1 point to your score. The game stops when there are fewer than two non-empty piles (meaning there are no more available moves).

Given three integers a, b, and c, return the maximum score you can get.

Example 1:

Input: a = 2, b = 4, c = 6

Output: 6

Explanation: The starting state is (2, 4, 6). One optimal set of moves is:

• Take from 1st and 3rd piles, state is now (1, 4, 5)
• Take from 1st and 3rd piles, state is now (0, 4, 4)
• Take from 2nd and 3rd piles, state is now (0, 3, 3)
• Take from 2nd and 3rd piles, state is now (0, 2, 2)
• Take from 2nd and 3rd piles, state is now (0, 1, 1)
• Take from 2nd and 3rd piles, state is now (0, 0, 0)

There are fewer than two non-empty piles, so the game ends. Total: 6 points.

Example 2:

Input: a = 4, b = 4, c = 6

Output: 7

Explanation: The starting state is (4, 4, 6). One optimal set of moves is:

• Take from 1st and 2nd piles, state is now (3, 3, 6)
• Take from 1st and 3rd piles, state is now (2, 3, 5)
• Take from 1st and 3rd piles, state is now (1, 3, 4)
• Take from 1st and 3rd piles, state is now (0, 3, 3)
• Take from 2nd and 3rd piles, state is now (0, 2, 2)
• Take from 2nd and 3rd piles, state is now (0, 1, 1)
• Take from 2nd and 3rd piles, state is now (0, 0, 0)

There are fewer than two non-empty piles, so the game ends. Total: 7 points.

Example 3:

Input: a = 1, b = 8, c = 8

Output: 8

Explanation: One optimal set of moves is to take from the 2nd and 3rd piles for 8 turns until they are empty.

After that, there are fewer than two non-empty piles, so the game ends.

Constraints:

• 1 <= a, b, c <= 10^5

Solution

Use a greedy approach. Use a priority queue to store the three pile sizes, where the maximum element is polled first. Offer a, b, and c to the priority queue. While the priority queue has at least 2 elements, poll 2 elements, decrease them by 1, and offer them back to the priority queue if they are greater than 0. Each time increase the score by 1. Finally, return the score.

• class Solution {
public int maximumScore(int a, int b, int c) {
int score = 0;
PriorityQueue<Integer> priorityQueue = new PriorityQueue<Integer>(new Comparator<Integer>() {
public int compare(Integer num1, Integer num2) {
return num2 - num1;
}
});
priorityQueue.offer(a);
priorityQueue.offer(b);
priorityQueue.offer(c);
while (priorityQueue.size() > 1) {
int num1 = priorityQueue.poll() - 1;
int num2 = priorityQueue.poll() - 1;
score++;
if (num1 > 0)
priorityQueue.offer(num1);
if (num2 > 0)
priorityQueue.offer(num2);
}
return score;
}
}

• Todo

• # 1753. Maximum Score From Removing Stones
# https://leetcode.com/problems/maximum-score-from-removing-stones

from heapq import heappush, heappop, heapify
​
class Solution:
# heap
def maximumScore(self, a: int, b: int, c: int) -> int:
res = 0
stones = [-a,-b,-c]
heapify(stones)

while abs(stones[0]) > 0 and abs(stones[1]) > 0:
first = heappop(stones) + 1
second = heappop(stones) + 1

heappush(stones, first)
heappush(stones, second)

res += 1

return res

# reverse engineering / math
def maximumScore(self, a: int, b: int, c: int) -> int:
return min((a+b+c)//2 , a+b+c - max(a,b,c))