Heap / Priority Queue

Last Stone Weight

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Question

You are given an array of integers stones where stones[i] is the weight of the ith stone.

We are playing a game with the stones. On each turn, we choose the heaviest two stones and smash them together. Suppose the heaviest two stones have weights x and y with x <= y. The result of this smash is:

  • If x == y, both stones are destroyed, and
  • If x != y, the stone of weight x is destroyed, and the stone of weight y has new weight y - x.

At the end of the game, there is at most one stone left.

Return the weight of the last remaining stone. If there are no stones left, return 0.

 

Example 1:

Input: stones = [2,7,4,1,8,1]
Output: 1
Explanation: 
We combine 7 and 8 to get 1 so the array converts to [2,4,1,1,1] then,
we combine 2 and 4 to get 2 so the array converts to [2,1,1,1] then,
we combine 2 and 1 to get 1 so the array converts to [1,1,1] then,
we combine 1 and 1 to get 0 so the array converts to [1] then that's the value of the last stone.

Example 2:

Input: stones = [1]
Output: 1

 

Constraints:

  • 1 <= stones.length <= 30
  • 1 <= stones[i] <= 1000

Code

				
					 public int lastStoneWeight(int[] stones) {
        PriorityQueue<Integer> minHeap = new PriorityQueue<>();
        for (int s : stones) {
            minHeap.offer(-s);
        }

        while (minHeap.size() > 1) {
            int first = minHeap.poll();
            int second = minHeap.poll();
            if (second > first) {
                minHeap.offer(first - second);
            }
        }

        minHeap.offer(0);
        return Math.abs(minHeap.peek());
    }
				
			

Convert All Weights to Negative:

 

				
					for (int s : stones) {
    minHeap.offer(-s);
}

				
			
  • We iterate over each stone in the array stones and insert its negative value into the minHeap. By storing negative weights, the min-heap will effectively behave like a max-heap, because the smallest value in a min-heap will correspond to the largest (positive) stone weight.

Smash the Two Heaviest Stones

				
					while (minHeap.size() > 1) {
    int first = minHeap.poll();
    int second = minHeap.poll();
    if (second > first) {
        minHeap.offer(first - second);
    }
}

				
			
  • The loop continues until there is one or zero stones left in the heap.
  • In each iteration, the two heaviest stones (i.e., the two smallest negative numbers in the heap) are removed using minHeap.poll().
    • first and second represent the two heaviest stones (in negative values).
  • If the stones have different weights (i.e., second > first), the difference between their negative values (first - second) is added back to the heap, which simulates keeping the remaining weight after smashing.

Handle the Remaining Stone

				
					minHeap.offer(0);
return Math.abs(minHeap.peek());

				
			
  • If no stones are left, the heap will be empty, so we add 0 to the heap as a fallback in case there are no remaining stones.
  • The method then returns the absolute value of the top element in the heap (minHeap.peek()), which will either be the weight of the last stone or 0.

Example Walkthrough:

Let’s take an example:

  • Input: stones = [2, 7, 4, 1, 8, 1]
  1. We push negative values into the heap: [-2, -7, -4, -1, -8, -1].

    • Heap (max-heap simulated with negatives): [-8, -7, -4, -1, -2, -1]
  2. First iteration:

    • Poll the two heaviest stones (-8, -7) → Original weights are 8 and 7.
    • Smash them: 8 - 7 = 1 → Add -1 back to the heap.
    • Heap: [-4, -2, -1, -1, -1]
  3. Second iteration:

    • Poll the two heaviest stones (-4, -2) → Original weights are 4 and 2.
    • Smash them: 4 - 2 = 2 → Add -2 back to the heap.
    • Heap: [-2, -1, -1, -1]
  4. Third iteration:

    • Poll the two heaviest stones (-2, -1) → Original weights are 2 and 1.
    • Smash them: 2 - 1 = 1 → Add -1 back to the heap.
    • Heap: [-1, -1, -1]
  5. Fourth iteration:

    • Poll the two heaviest stones (-1, -1) → Original weights are 1 and 1.
    • Both stones are destroyed since they are equal, so no new stone is added back.
    • Heap: [-1]
  6. Final:

    • Only one stone remains, so the loop exits.
    • Return the absolute value of the last stone: | -1 | = 1.

Summary of Key Operations:

  • The min-heap is used to simulate a max-heap by storing negative weights.
  • The two heaviest stones are repeatedly smashed together, and if one remains, it is added back to the heap.
  • The process continues until one or no stones remain, and the result is the weight of the last remaining stone (or 0 if none).
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