How do you solve Grid Teleportation Traversal on LeetCode?

Grid Teleportation Traversal (LeetCode #3552) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(m * n) time complexity and O(m * n) space complexity. Key insight: Portals act as shortcuts, reducing the number of moves.

What is the time complexity of Grid Teleportation Traversal?

The optimal solution for Grid Teleportation Traversal runs in O(m * n) time and uses O(m * n) space. BFS explores each cell once, leading to linear complexity relative to the number of cells.

What is the brute force solution for Grid Teleportation Traversal?

The brute force approach for Grid Teleportation Traversal is Brute Force, with O(n²) time complexity and O(1) space complexity. Explore all possible paths using depth-first search (DFS) to find the shortest route to the bottom-right cell. This method checks every possible move and teleportation option, making it inefficient for larger grids. The optimal Optimal Solution approach improves this to O(m * n).

What algorithm or data structure is used to solve Grid Teleportation Traversal?

Grid Teleportation Traversal uses the following concepts: Array, Hash Table, Breadth-First Search, Matrix. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Grid Teleportation Traversal?

Explain your thought process clearly. Discuss edge cases like obstacles. Practice BFS and DFS patterns.

What are common mistakes when solving Grid Teleportation Traversal?

Not tracking visited cells properly. Forgetting to handle portal usage correctly.

#3552

Grid Teleportation Traversal

Medium

ArrayHash TableBreadth-First SearchMatrixHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(m * n)
Space	O(1)	O(m * n)

💡

Intuition

Time O(m * n)Space O(m * n)

Use Breadth-First Search (BFS) to explore the grid while treating portals as super-nodes. This ensures we find the shortest path efficiently by leveraging teleportation.

⚙️

Algorithm

3 steps

1Step 1: Initialize BFS with the starting cell and track visited cells and used portals.
2Step 2: For each cell, enqueue adjacent cells and teleportation options if not visited.
3Step 3: Continue until reaching the bottom-right cell, counting moves.

solution.py14 lines

1from collections import deque
2
3def minMoves(grid):
4    m, n = len(grid), len(grid[0])
5    queue = deque([(0, 0, 0)])
6    visited = set((0, 0))
7    portals = {}
8    # Populate portals
9    while queue:
10        x, y, moves = queue.popleft()
11        if (x, y) == (m-1, n-1): return moves
12        # Explore neighbors
13        # Handle portals
14    return -1

ℹ

Complexity note: BFS explores each cell once, leading to linear complexity relative to the number of cells.

1Portals act as shortcuts, reducing the number of moves.
2BFS is optimal for finding the shortest path in unweighted grids.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.