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2617. Minimum Number of Visited Cells in a Grid

Description

You are given a 0-indexed m x n integer matrix grid. Your initial position is at the top-left cell (0, 0).

Starting from the cell (i, j), you can move to one of the following cells:

  • Cells (i, k) with j < k <= grid[i][j] + j (rightward movement), or
  • Cells (k, j) with i < k <= grid[i][j] + i (downward movement).

Return the minimum number of cells you need to visit to reach the bottom-right cell (m - 1, n - 1). If there is no valid path, return -1.

 

Example 1:

Input: grid = [[3,4,2,1],[4,2,3,1],[2,1,0,0],[2,4,0,0]]
Output: 4
Explanation: The image above shows one of the paths that visits exactly 4 cells.

Example 2:

Input: grid = [[3,4,2,1],[4,2,1,1],[2,1,1,0],[3,4,1,0]]
Output: 3
Explanation: The image above shows one of the paths that visits exactly 3 cells.

Example 3:

Input: grid = [[2,1,0],[1,0,0]]
Output: -1
Explanation: It can be proven that no path exists.

 

Constraints:

  • m == grid.length
  • n == grid[i].length
  • 1 <= m, n <= 105
  • 1 <= m * n <= 105
  • 0 <= grid[i][j] < m * n
  • grid[m - 1][n - 1] == 0

Solutions

Solution 1: Priority Queue

Let's denote the number of rows of the grid as $m$ and the number of columns as $n$. Define $dist[i][j]$ to be the shortest distance from the coordinate $(0, 0)$ to the coordinate $(i, j)$. Initially, $dist[0][0]=1$ and $dist[i][j]=-1$ for all other $i$ and $j$.

For each grid $(i, j)$, it can come from the grid above or the grid on the left. If it comes from the grid above $(i', j)$, where $0 \leq i' \lt i$, then $(i', j)$ must satisfy $grid[i'][j] + i' \geq i$. We need to select from these grids the one that is closest.

Therefore, we maintain a priority queue (min-heap) for each column $j$. Each element of the priority queue is a pair $(dist[i][j], i)$, which represents that the shortest distance from the coordinate $(0, 0)$ to the coordinate $(i, j)$ is $dist[i][j]$. When we consider the coordinate $(i, j)$, we only need to take out the head element $(dist[i'][j], i')$ of the priority queue. If $grid[i'][j] + i' \geq i$, we can move from the coordinate $(i', j)$ to the coordinate $(i, j)$. At this time, we can update the value of $dist[i][j]$, that is, $dist[i][j] = dist[i'][j] + 1$, and add $(dist[i][j], i)$ to the priority queue.

Similarly, we can maintain a priority queue for each row $i$ and perform a similar operation.

Finally, we can obtain the shortest distance from the coordinate $(0, 0)$ to the coordinate $(m - 1, n - 1)$, that is, $dist[m - 1][n - 1]$, which is the answer.

The time complexity is $O(m \times n \times \log (m \times n))$ and the space complexity is $O(m \times n)$. Here, $m$ and $n$ are the number of rows and columns of the grid, respectively.

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class Solution:
    def minimumVisitedCells(self, grid: List[List[int]]) -> int:
        m, n = len(grid), len(grid[0])
        dist = [[-1] * n for _ in range(m)]
        dist[0][0] = 1
        row = [[] for _ in range(m)]
        col = [[] for _ in range(n)]
        for i in range(m):
            for j in range(n):
                while row[i] and grid[i][row[i][0][1]] + row[i][0][1] < j:
                    heappop(row[i])
                if row[i] and (dist[i][j] == -1 or dist[i][j] > row[i][0][0] + 1):
                    dist[i][j] = row[i][0][0] + 1
                while col[j] and grid[col[j][0][1]][j] + col[j][0][1] < i:
                    heappop(col[j])
                if col[j] and (dist[i][j] == -1 or dist[i][j] > col[j][0][0] + 1):
                    dist[i][j] = col[j][0][0] + 1
                if dist[i][j] != -1:
                    heappush(row[i], (dist[i][j], j))
                    heappush(col[j], (dist[i][j], i))
        return dist[-1][-1]

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class Solution {
    public int minimumVisitedCells(int[][] grid) {
        int m = grid.length, n = grid[0].length;
        int[][] dist = new int[m][n];
        PriorityQueue<int[]>[] row = new PriorityQueue[m];
        PriorityQueue<int[]>[] col = new PriorityQueue[n];
        for (int i = 0; i < m; ++i) {
            Arrays.fill(dist[i], -1);
            row[i] = new PriorityQueue<>((a, b) -> a[0] == b[0] ? a[1] - b[1] : a[0] - b[0]);
        }
        for (int i = 0; i < n; ++i) {
            col[i] = new PriorityQueue<>((a, b) -> a[0] == b[0] ? a[1] - b[1] : a[0] - b[0]);
        }
        dist[0][0] = 1;
        for (int i = 0; i < m; ++i) {
            for (int j = 0; j < n; ++j) {
                while (!row[i].isEmpty() &&