How do you solve Minimum Moves to Clean the Classroom on LeetCode?

Minimum Moves to Clean the Classroom (LeetCode #3568) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n*m*2^k) time complexity and O(n*m*2^k) space complexity. Key insight: BFS is effective for shortest path problems in grids.

What is the time complexity of Minimum Moves to Clean the Classroom?

The optimal solution for Minimum Moves to Clean the Classroom runs in O(n*m*2^k) time and uses O(n*m*2^k) space. The complexity accounts for exploring each cell and all combinations of collected litter (k is the number of litter pieces).

What is the brute force solution for Minimum Moves to Clean the Classroom?

The brute force approach for Minimum Moves to Clean the Classroom is Brute Force, with O(n²) time complexity and O(1) space complexity. Explore all possible paths from the starting position to collect litter, checking each cell and backtracking as needed. This method is inefficient as it doesn't optimize for energy usage or obstacles. The optimal Optimal Solution approach improves this to O(n*m*2^k).

What are the interview tips for Minimum Moves to Clean the Classroom?

Explain your thought process clearly. Discuss edge cases and how to handle them. Practice similar grid problems to build intuition.

What are common mistakes when solving Minimum Moves to Clean the Classroom?

Forgetting to reset energy on 'R'. Not pruning states with lower energy.

#3568

Minimum Moves to Clean the Classroom

Medium

ArrayHash TableBit ManipulationBreadth-First SearchMatrixHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(nm2^k)
Space	O(1)	O(nm2^k)

💡

Intuition

Time O(n*m*2^k)Space O(n*m*2^k)

Use BFS to explore the grid while tracking energy and collected litter efficiently. This approach minimizes redundant states and ensures we only explore viable paths.

⚙️

Algorithm

3 steps

1Step 1: Initialize BFS with the starting position, energy, and a bitmask for collected litter.
2Step 2: For each position, explore adjacent cells, updating energy and litter mask accordingly.
3Step 3: Use a 3D array to prune states with lower energy to avoid unnecessary exploration.

solution.py5 lines

1from collections import deque
2
3def minMoves(grid, energy):
4    # BFS implementation omitted for brevity
5    pass

ℹ

Complexity note: The complexity accounts for exploring each cell and all combinations of collected litter (k is the number of litter pieces).

1BFS is effective for shortest path problems in grids.
2Using bitmasking helps efficiently track collected items.

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