Data una matrice rettangolare mat[][] dove alcune celle contengono mine (indicate con 0) e le restanti sono sicure (indicate con 1), trova la lunghezza del percorso sicuro più breve da qualsiasi cella nella prima colonna a qualsiasi cella nell'ultima colonna.
- Le mine terrestri non sono sicure e anche le loro quattro celle adiacenti (in alto in basso a sinistra a destra) non sono sicure.
- Sono consentiti solo movimenti orizzontali e verticali verso celle sicure adiacenti.
- Se è impossibile raggiungere l'ultima colonna in sicurezza, restituisci -1.
Esempi:
Ingresso:
con[][] = [ [1 0 1 1 1]
[1 1 1 1 1]
[1 1 1 1 1]
[1 1 1 0 1]
[1 1 1 1 0] ]
Produzione: 6
Spiegazione:
Possiamo vedere la lunghezza più breve
il percorso sicuro è 6.
Ingresso:
con[][] = [ [1 1 1 1 1]
[1 1 0 1 1]
[1 1 1 1 1] ]
Produzione: -1
Spiegazione: Non esiste un percorso possibile da
dalla prima colonna all'ultima colonna.
Sommario
[Approccio] Utilizzo del Backtracking
C++L'idea è usare Fare marcia indietro . Per prima cosa contrassegniamo come non sicure tutte le celle adiacenti delle mine antiuomo. Quindi per ogni cella sicura della prima colonna della matrice andiamo avanti in tutte le direzioni consentite e controlliamo ricorsivamente se portano a destinazione o meno. Se viene trovata la destinazione, aggiorniamo il valore del percorso più breve, altrimenti se nessuna delle soluzioni di cui sopra funziona, restituiamo false dalla nostra funzione.
#include
import java.util.Arrays; class Solution { // Function to mark unsafe cells (landmines and their adjacent cells) private void markUnsafeCells(int[][] mat) { int r = mat.length; int c = mat[0].length; int[] row = {-1 1 0 0}; int[] col = {0 0 -1 1}; // Create a copy to avoid modifying original safe cells prematurely int[][] temp = new int[r][c]; for (int i = 0; i < r; i++) { for (int j = 0; j < c; j++) { temp[i][j] = mat[i][j]; } } // Mark adjacent cells of landmines (0) as unsafe (0) for (int i = 0; i < r; i++) { for (int j = 0; j < c; j++) { if (temp[i][j] == 0) { for (int k = 0; k < 4; k++) { int ni = i + row[k]; int nj = j + col[k]; if (ni >= 0 && ni < r && nj >= 0 && nj < c) { mat[ni][nj] = 0; } } } } } } // DFS to find shortest path from (i j) to any cell in last column private int dfs(int[][] mat boolean[][] visited int i int j int c) { int r = mat.length; // If out of bounds blocked or visited if (i < 0 || i >= r || j < 0 || j >= c || mat[i][j] == 0 || visited[i][j]) { return Integer.MAX_VALUE; } if (j == c - 1) { return 1; } visited[i][j] = true; int[] row = {-1 1 0 0}; int[] col = {0 0 -1 1}; int minPath = Integer.MAX_VALUE; // Try all four directions for (int k = 0; k < 4; k++) { int ni = i + row[k]; int nj = j + col[k]; int pathLength = dfs(mat visited ni nj c); if (pathLength != Integer.MAX_VALUE) { minPath = Math.min(minPath 1 + pathLength); } } // Backtrack - unmark current cell visited[i][j] = false; return minPath; } public int findShortestPath(int[][] mat) { int r = mat.length; int c = mat[0].length; // Mark all adjacent cells of landmines as unsafe markUnsafeCells(mat); boolean[][] visited = new boolean[r][c]; int minPath = Integer.MAX_VALUE; // Try starting from each safe cell in the first column for (int i = 0; i < r; i++) { if (mat[i][0] == 1) { int pathLength = dfs(mat visited i 0 c); if (pathLength != Integer.MAX_VALUE) { minPath = Math.min(minPath pathLength); } } } return minPath == Integer.MAX_VALUE ? -1 : minPath; } public static void main(String[] args) { int[][] mat = { {1 0 1 1 1} {1 1 1 1 1} {1 1 1 1 1} {1 1 1 0 1} {1 1 1 1 0} }; Solution solution = new Solution(); int result = solution.findShortestPath(mat); System.out.println(result); } }
# Function to mark unsafe cells (landmines and their adjacent cells) def mark_unsafe_cells(mat): r = len(mat) c = len(mat[0]) # Directions for adjacent cells: up down left right row = [-1 1 0 0] col = [0 0 -1 1] # Create a copy to avoid modifying original safe cells prematurely temp = [row[:] for row in mat] # Mark adjacent cells of landmines (0) as unsafe (0) for i in range(r): for j in range(c): if temp[i][j] == 0: for k in range(4): ni = i + row[k] nj = j + col[k] if 0 <= ni < r and 0 <= nj < c: mat[ni][nj] = 0 # DFS to find shortest path from (i j) to any cell in last column def dfs(mat visited i j c): r = len(mat) # If out of bounds blocked or visited if i < 0 or i >= r or j < 0 or j >= c or mat[i][j] == 0 or visited[i][j]: return float('inf') if j == c - 1: return 1 visited[i][j] = True # Four possible moves: up down left right row = [-1 1 0 0] col = [0 0 -1 1] min_path = float('inf') # Try all four directions for k in range(4): ni = i + row[k] nj = j + col[k] path_length = dfs(mat visited ni nj c) if path_length != float('inf'): min_path = min(min_path 1 + path_length) # Backtrack - unmark current cell visited[i][j] = False return min_path def findShortestPath(mat): r = len(mat) c = len(mat[0]) # Mark all adjacent cells of landmines as unsafe mark_unsafe_cells(mat) visited = [[False] * c for _ in range(r)] min_path = float('inf') # Try starting from each safe cell in the first column for i in range(r): if mat[i][0] == 1: path_length = dfs(mat visited i 0 c) if path_length != float('inf'): min_path = min(min_path path_length) return -1 if min_path == float('inf') else min_path def main(): mat = [ [1 0 1 1 1] [1 1 1 1 1] [1 1 1 1 1] [1 1 1 0 1] [1 1 1 1 0] ] result = findShortestPath(mat) print(result) if __name__ == '__main__': main()
using System; class GFG { // Function to mark unsafe cells (landmines and their adjacent cells) private void MarkUnsafeCells(int[][] mat) { int r = mat.Length; int c = mat[0].Length; // Directions for adjacent cells: up down left right int[] row = { -1 1 0 0 }; int[] col = { 0 0 -1 1 }; // Create a copy to avoid modifying original safe cells prematurely int[][] temp = new int[r][]; for (int i = 0; i < r; i++) { temp[i] = new int[c]; Array.Copy(mat[i] temp[i] c); } // Mark adjacent cells of landmines (0) as unsafe (0) for (int i = 0; i < r; i++) { for (int j = 0; j < c; j++) { if (temp[i][j] == 0) { for (int k = 0; k < 4; k++) { int ni = i + row[k]; int nj = j + col[k]; if (ni >= 0 && ni < r && nj >= 0 && nj < c) { mat[ni][nj] = 0; } } } } } } // DFS to find shortest path from (i j) to any cell in last column private int Dfs(int[][] mat bool[][] visited int i int j int c) { int r = mat.Length; // If out of bounds blocked or visited if (i < 0 || i >= r || j < 0 || j >= c || mat[i][j] == 0 || visited[i][j]) { return int.MaxValue; } if (j == c - 1) { return 1; } visited[i][j] = true; int[] row = { -1 1 0 0 }; int[] col = { 0 0 -1 1 }; int minPath = int.MaxValue; // Try all four directions for (int k = 0; k < 4; k++) { int ni = i + row[k]; int nj = j + col[k]; int pathLength = Dfs(mat visited ni nj c); if (pathLength != int.MaxValue) { minPath = Math.Min(minPath 1 + pathLength); } } // Backtrack - unmark current cell visited[i][j] = false; return minPath; } public int FindShortestPath(int[][] mat) { int r = mat.Length; int c = mat[0].Length; // Mark all adjacent cells of landmines as unsafe MarkUnsafeCells(mat); bool[][] visited = new bool[r][]; for (int i = 0; i < r; i++) { visited[i] = new bool[c]; } int minPath = int.MaxValue; // Try starting from each safe cell in the first column for (int i = 0; i < r; i++) { if (mat[i][0] == 1) { int pathLength = Dfs(mat visited i 0 c); if (pathLength != int.MaxValue) { minPath = Math.Min(minPath pathLength); } } } return minPath == int.MaxValue ? -1 : minPath; } static void Main(string[] args) { int[][] mat = new int[][] { new int[] { 1 0 1 1 1 } new int[] { 1 1 1 1 1 } new int[] { 1 1 1 1 1 } new int[] { 1 1 1 0 1 } new int[] { 1 1 1 1 0 } }; GFG solution = new GFG(); int result = solution.FindShortestPath(mat); Console.WriteLine(result); } }
function markUnsafeCells(mat) { const r = mat.length; const c = mat[0].length; // Directions for adjacent cells: up down left right const row = [-1 1 0 0]; const col = [0 0 -1 1]; // Create a copy to avoid modifying original safe cells prematurely const temp = mat.map(row => [...row]); // Mark adjacent cells of landmines (0) as unsafe (0) for (let i = 0; i < r; i++) { for (let j = 0; j < c; j++) { if (temp[i][j] === 0) { for (let k = 0; k < 4; k++) { const ni = i + row[k]; const nj = j + col[k]; if (ni >= 0 && ni < r && nj >= 0 && nj < c) { mat[ni][nj] = 0; } } } } } } function dfs(mat visited i j c) { const r = mat.length; // If out of bounds blocked or visited if (i < 0 || i >= r || j < 0 || j >= c || mat[i][j] === 0 || visited[i][j]) { return Infinity; } // If reached the last column if (j === c - 1) { return 1; } visited[i][j] = true; const row = [-1 1 0 0]; const col = [0 0 -1 1]; let minPath = Infinity; // Try all four directions for (let k = 0; k < 4; k++) { const ni = i + row[k]; const nj = j + col[k]; const pathLength = dfs(mat visited ni nj c); if (pathLength !== Infinity) { minPath = Math.min(minPath 1 + pathLength); } } // Backtrack - unmark current cell visited[i][j] = false; return minPath; } function findShortestPath(mat) { const r = mat.length; const c = mat[0].length; // Mark all adjacent cells of landmines as unsafe markUnsafeCells(mat); const visited = Array(r).fill().map(() => Array(c).fill(false)); let minPath = Infinity; // Try starting from each safe cell in the first column for (let i = 0; i < r; i++) { if (mat[i][0] === 1) { const pathLength = dfs(mat visited i 0 c); if (pathLength !== Infinity) { minPath = Math.min(minPath pathLength); } } } return minPath === Infinity ? -1 : minPath; } const mat = [ [1 0 1 1 1] [1 1 1 1 1] [1 1 1 1 1] [1 1 1 0 1] [1 1 1 1 0] ]; const result = findShortestPath(mat); console.log(result);
Produzione
6
Complessità temporale: O(4^(r * c)) dove r è il numero di righe e c è il numero di colonne nella matrice data.
Spazio ausiliario: O(r*c) poiché stiamo utilizzando spazio extra come visitato[r][c].
[Approccio ottimizzato] Utilizzo della ricerca in ampiezza
C++Può essere risolto in tempo polinomiale utilizzando la ricerca in ampiezza. Accoda tutte le celle sicure dall'ultima colonna nella coda con distanza = 1. Mentre BFS procede, viene calcolato il percorso più breve per ciascuna cella dall'ultima colonna. Infine tra tutte le celle raggiungibili nella prima colonna viene visualizzata la distanza minima.
#include
import java.util.*; public class Solution { static int[] rowNum = {-1 0 0 1}; static int[] colNum = {0 -1 1 0}; public static int findShortestPath(int[][] mat) { int n = mat.length; int m = mat[0].length; Queue<int[]> q = new LinkedList<>(); int[][] d = new int[n][m]; // Initializing distance array with large values for (int i = 0; i < n; i++) { Arrays.fill(d[i] (int) 1e9); } // Lambda-like helper function: check if cell is valid java.util.function.BiFunction<Integer Integer Boolean> isValid = (i j) -> { return !(i < 0 || i >= n || j < 0 || j >= m); }; // Helper function: check if cell and adjacent cells are safe java.util.function.BiFunction<Integer Integer Boolean> check = (i j) -> { if (!isValid.apply(i j)) return false; for (int k = 0; k < 4; k++) { int ni = i + rowNum[k]; int nj = j + colNum[k]; if (isValid.apply(ni nj) && mat[ni][nj] == 0) return false; } return true; }; // Pushing cells from the rightmost column into the queue for (int i = 0; i < n; i++) { if (check.apply(i m - 1)) { q.add(new int[]{i m - 1 1}); } } // BFS traversal while (!q.isEmpty()) { int[] z = q.poll(); int x = z[0] y = z[1] dis = z[2]; if (d[x][y] > dis) { d[x][y] = dis; for (int k = 0; k < 4; k++) { int ni = x + rowNum[k]; int nj = y + colNum[k]; if (check.apply(ni nj)) { q.add(new int[]{ni nj dis + 1}); } } } } // Finding the minimum distance in the first column int ans = (int) 1e9; for (int i = 0; i < n; i++) { ans = Math.min(ans d[i][0]); } // If no safe path found return -1 if (ans >= 1e9) ans = -1; return ans; } public static void main(String[] args) { int[][] mat = { {1 0 1 1 1} {1 1 1 1 1} {1 1 1 1 1} {1 1 1 0 1} {1 1 1 1 0} }; int result = findShortestPath(mat); System.out.println(result); } }
from collections import deque rowNum = [-1 0 0 1] colNum = [0 -1 1 0] def findShortestPath(mat): n = len(mat) m = len(mat[0]) q = deque() d = [[10**9 for _ in range(m)] for _ in range(n)] # Check if cell is valid def isValid(i j): return not (i < 0 or i >= n or j < 0 or j >= m) # Check if cell and its adjacent cells are safe def check(i j): if not isValid(i j): return False for k in range(4): ni nj = i + rowNum[k] j + colNum[k] if isValid(ni nj) and mat[ni][nj] == 0: return False return True # Pushing cells from the rightmost column into the queue for i in range(n): if check(i m - 1): q.append((i m - 1 1)) # BFS traversal while q: x y dis = q.popleft() if d[x][y] > dis: d[x][y] = dis for k in range(4): ni nj = x + rowNum[k] y + colNum[k] if check(ni nj): q.append((ni nj dis + 1)) # Finding the minimum distance in the first column ans = min(d[i][0] for i in range(n)) # If no safe path found return -1 if ans >= 10**9: ans = -1 return ans if __name__ == '__main__': mat = [ [1 0 1 1 1] [1 1 1 1 1] [1 1 1 1 1] [1 1 1 0 1] [1 1 1 1 0] ] result = findShortestPath(mat) print(result)
using System; using System.Collections.Generic; class Solution { static int[] rowNum = { -1 0 0 1 }; static int[] colNum = { 0 -1 1 0 }; // Check if cell is valid static bool IsValid(int i int j int n int m) { return !(i < 0 || i >= n || j < 0 || j >= m); } // Check if cell and its adjacent cells are safe static bool Check(int i int j int[][] mat int n int m) { if (!IsValid(i j n m)) return false; for (int k = 0; k < 4; k++) { int ni = i + rowNum[k]; int nj = j + colNum[k]; if (IsValid(ni nj n m) && mat[ni][nj] == 0) return false; } return true; } public static int FindShortestPath(int[][] mat) { int n = mat.Length; int m = mat[0].Length; Queue<(int int int)> q = new Queue<(int int int)>(); int[] d = new int[n m]; // Initialize distance array with large value for (int i = 0; i < n; i++) for (int j = 0; j < m; j++) d[i j] = int.MaxValue / 2; // Push safe cells from rightmost column for (int i = 0; i < n; i++) { if (Check(i m - 1 mat n m)) { q.Enqueue((i m - 1 1)); } } // BFS traversal while (q.Count > 0) { var (x y dis) = q.Dequeue(); if (d[x y] > dis) { d[x y] = dis; for (int k = 0; k < 4; k++) { int ni = x + rowNum[k]; int nj = y + colNum[k]; if (Check(ni nj mat n m)) { q.Enqueue((ni nj dis + 1)); } } } } // Find minimum distance in the first column int ans = int.MaxValue / 2; for (int i = 0; i < n; i++) ans = Math.Min(ans d[i 0]); return ans >= int.MaxValue / 2 ? -1 : ans; } static void Main() { int[][] mat = new int[][] { new int[] {1 0 1 1 1} new int[] {1 1 1 1 1} new int[] {1 1 1 1 1} new int[] {1 1 1 0 1} new int[] {1 1 1 1 0} }; int result = FindShortestPath(mat); Console.WriteLine(result); } }
function findShortestPath(mat) { const n = mat.length; const m = mat[0].length; const rowNum = [-1 0 0 1]; const colNum = [0 -1 1 0]; // Distance matrix initialized to large value const d = Array.from({ length: n } () => Array(m).fill(Number.MAX_SAFE_INTEGER)); // Check if cell is valid function isValid(i j) { return !(i < 0 || i >= n || j < 0 || j >= m); } // Check if cell and its adjacent cells are safe function check(i j) { if (!isValid(i j)) return false; for (let k = 0; k < 4; k++) { let ni = i + rowNum[k]; let nj = j + colNum[k]; if (isValid(ni nj) && mat[ni][nj] === 0) return false; } return true; } // Queue for BFS let q = []; // Push safe cells from rightmost column for (let i = 0; i < n; i++) { if (check(i m - 1)) { q.push([i m - 1 1]); } } // BFS traversal while (q.length > 0) { let [x y dis] = q.shift(); if (d[x][y] > dis) { d[x][y] = dis; for (let k = 0; k < 4; k++) { let ni = x + rowNum[k]; let nj = y + colNum[k]; if (check(ni nj)) { q.push([ni nj dis + 1]); } } } } // Find minimum distance in first column let ans = Number.MAX_SAFE_INTEGER; for (let i = 0; i < n; i++) { ans = Math.min(ans d[i][0]); } return ans >= Number.MAX_SAFE_INTEGER ? -1 : ans; } const mat = [ [1 0 1 1 1] [1 1 1 1 1] [1 1 1 1 1] [1 1 1 0 1] [1 1 1 1 0] ]; const result = findShortestPath(mat); console.log(result);
Produzione
6
Complessità temporale: O(r * c) dove r e c sono rispettivamente il numero di righe e colonne nella matrice data.
Spazio ausiliario: O(r*c)