LeetCode 2931: Maximum Spending After Buying Items Solution

Master LeetCode problem 2931 (Maximum Spending After Buying Items), a hard challenge, with our optimized solutions in Java, C++, and Python. Explore detailed explanations, test your code in our interactive editor, and prepare for coding interviews.

2931. Maximum Spending After Buying Items

Hard

Array Greedy Sorting Heap (Priority Queue)Matrix

Problem Explanation

Explanation

To solve this problem, we need to simulate the buying process day by day and track the maximum spending possible. We can achieve this by maintaining a priority queue (min-heap) where we store the negative values along with the indices. At each day, we pop the maximum negative value from the priority queue, calculate the spending, update the maximum spending, and push the next available item from the same shop back to the priority queue. We repeat this process for d days.

Time Complexity: O(m * n * log(n)), where m is the number of shops and n is the number of items in each shop. Space Complexity: O(n) for the priority queue.

Solution Code

import java.util.PriorityQueue;

class Solution {
    public int maxProfit(int[][] values) {
        int m = values.length;
        int n = values[0].length;
        
        PriorityQueue<int[]> pq = new PriorityQueue<>((a, b) -> b[0] - a[0]);
        
        for (int i = 0; i < m; i++) {
            pq.offer(new int[]{values[i][0], i, 0});
        }
        
        int maxSpending = 0;
        
        for (int d = 1; d <= m * n; d++) {
            int[] curr = pq.poll();
            maxSpending += curr[0] * d;
            
            if (curr[2] < n - 1) {
                int nextIndex = curr[2] + 1;
                pq.offer(new int[]{values[curr[1]][nextIndex], curr[1], nextIndex});
            }
        }
        
        return maxSpending;
    }
}

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