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Percorso più lungo possibile in una matrice con ostacoli

Provalo su GfG Practice Percorso più lungo possibile in una matrice con ostacoli' title=

Data una matrice binaria 2D insieme a[][] dove alcune celle sono ostacoli (indicati da0) e il resto sono celle libere (indicate da1) il tuo compito è trovare la lunghezza del percorso più lungo possibile da una cella di origine (xs ys) a una cella di destinazione (xd yd) .

  • Puoi spostarti solo nelle celle adiacenti (su giù a sinistra a destra).
  • Non sono consentiti spostamenti diagonali.
  • Una cella una volta visitata in un percorso non può essere rivisitata in quello stesso percorso.
  • Se è impossibile raggiungere la destinazione restituire-1.

Esempi:
Ingresso: xs = 0 ys = 0 xd = 1 yd = 7
con[][] = [ [1 1 1 1 1 1 1 1 1 1]
[1 1 0 1 1 0 1 1 0 1]
[1 1 1 1 1 1 1 1 1 1]]
Produzione: 24
Spiegazione:



Java matematica.min

Ingresso: xs = 0 ys = 3 xd = 2 yd = 2
con[][] =[ [1 0 0 1 0]
[0 0 0 1 0]
[0 1 1 0 0] ]
Produzione: -1
Spiegazione:
Possiamo vedere che è impossibile
raggiungere la cella (22) da (03).

Sommario



[Approccio] Utilizzo del Backtracking con Matrice Visitata

L'idea è usare Fare marcia indietro . Partiamo dalla cella sorgente della matrice, andiamo avanti in tutte e quattro le direzioni consentite e controlliamo ricorsivamente se portano o meno alla soluzione. Se la destinazione viene trovata aggiorniamo il valore del percorso più lungo altrimenti se nessuna delle soluzioni precedenti funziona restituiamo false dalla nostra funzione.

CPP 
#include    #include  #include  #include    using namespace std; // Function to find the longest path using backtracking int dfs(vector<vector<int>> &mat   vector<vector<bool>> &visited int i   int j int x int y) {  int m = mat.size();  int n = mat[0].size();    // If destination is reached  if (i == x && j == y) {  return 0;  }    // If cell is invalid blocked or already visited  if (i < 0 || i >= m || j < 0 || j >= n ||   mat[i][j] == 0 || visited[i][j]) {  return -1;   }    // Mark current cell as visited  visited[i][j] = true;    int maxPath = -1;    // Four possible moves: up down left right  int row[] = {-1 1 0 0};  int col[] = {0 0 -1 1};    for (int k = 0; k < 4; k++) {  int ni = i + row[k];  int nj = j + col[k];    int pathLength = dfs(mat visited   ni nj x y);    // If a valid path is found from this direction  if (pathLength != -1) {  maxPath = max(maxPath 1 + pathLength);  }  }    // Backtrack - unmark current cell  visited[i][j] = false;    return maxPath; } int findLongestPath(vector<vector<int>> &mat   int xs int ys int xd int yd) {  int m = mat.size();  int n = mat[0].size();    // Check if source or destination is blocked  if (mat[xs][ys] == 0 || mat[xd][yd] == 0) {  return -1;  }    vector<vector<bool>> visited(m vector<bool>(n false));  return dfs(mat visited xs ys xd yd); } int main() {  vector<vector<int>> mat = {  {1 1 1 1 1 1 1 1 1 1}  {1 1 0 1 1 0 1 1 0 1}  {1 1 1 1 1 1 1 1 1 1}  };    int xs = 0 ys = 0;   int xd = 1 yd = 7;     int result = findLongestPath(mat xs ys xd yd);    if (result != -1)  cout << result << endl;  else  cout << -1 << endl;    return 0; }
Java 
import java.util.Arrays; public class GFG {    // Function to find the longest path using backtracking  public static int dfs(int[][] mat boolean[][] visited  int i int j int x int y) {  int m = mat.length;  int n = mat[0].length;    // If destination is reached  if (i == x && j == y) {  return 0;  }    // If cell is invalid blocked or already visited  if (i < 0 || i >= m || j < 0 || j >= n || mat[i][j] == 0 || visited[i][j]) {  return -1; // Invalid path  }    // Mark current cell as visited  visited[i][j] = true;    int maxPath = -1;    // Four possible moves: up down left right  int[] row = {-1 1 0 0};  int[] col = {0 0 -1 1};    for (int k = 0; k < 4; k++) {  int ni = i + row[k];  int nj = j + col[k];    int pathLength = dfs(mat visited ni nj x y);    // If a valid path is found from this direction  if (pathLength != -1) {  maxPath = Math.max(maxPath 1 + pathLength);  }  }    // Backtrack - unmark current cell  visited[i][j] = false;    return maxPath;  }    public static int findLongestPath(int[][] mat int xs int ys int xd int yd) {  int m = mat.length;  int n = mat[0].length;    // Check if source or destination is blocked  if (mat[xs][ys] == 0 || mat[xd][yd] == 0) {  return -1;  }    boolean[][] visited = new boolean[m][n];  return dfs(mat visited xs ys xd yd);  }    public static void main(String[] args) {  int[][] mat = {  {1 1 1 1 1 1 1 1 1 1}  {1 1 0 1 1 0 1 1 0 1}  {1 1 1 1 1 1 1 1 1 1}  };    int xs = 0 ys = 0;  int xd = 1 yd = 7;    int result = findLongestPath(mat xs ys xd yd);    if (result != -1)  System.out.println(result);  else  System.out.println(-1);  } }
Python 
# Function to find the longest path using backtracking def dfs(mat visited i j x y): m = len(mat) n = len(mat[0]) # If destination is reached if i == x and j == y: return 0 # If cell is invalid blocked or already visited if i < 0 or i >= m or j < 0 or j >= n or mat[i][j] == 0 or visited[i][j]: return -1 # Invalid path # Mark current cell as visited visited[i][j] = True maxPath = -1 # Four possible moves: up down left right row = [-1 1 0 0] col = [0 0 -1 1] for k in range(4): ni = i + row[k] nj = j + col[k] pathLength = dfs(mat visited ni nj x y) # If a valid path is found from this direction if pathLength != -1: maxPath = max(maxPath 1 + pathLength) # Backtrack - unmark current cell visited[i][j] = False return maxPath def findLongestPath(mat xs ys xd yd): m = len(mat) n = len(mat[0]) # Check if source or destination is blocked if mat[xs][ys] == 0 or mat[xd][yd] == 0: return -1 visited = [[False for _ in range(n)] for _ in range(m)] return dfs(mat visited xs ys xd yd) def main(): mat = [ [1 1 1 1 1 1 1 1 1 1] [1 1 0 1 1 0 1 1 0 1] [1 1 1 1 1 1 1 1 1 1] ] xs ys = 0 0 xd yd = 1 7 result = findLongestPath(mat xs ys xd yd) if result != -1: print(result) else: print(-1) if __name__ == '__main__': main()
C# 
using System; class GFG {  // Function to find the longest path using backtracking  static int dfs(int[] mat bool[] visited   int i int j int x int y)  {  int m = mat.GetLength(0);  int n = mat.GetLength(1);    // If destination is reached  if (i == x && j == y)  {  return 0;  }    // If cell is invalid blocked or already visited  if (i < 0 || i >= m || j < 0 || j >= n || mat[i j] == 0 || visited[i j])  {  return -1; // Invalid path  }    // Mark current cell as visited  visited[i j] = true;    int maxPath = -1;    // Four possible moves: up down left right  int[] row = {-1 1 0 0};  int[] col = {0 0 -1 1};    for (int k = 0; k < 4; k++)  {  int ni = i + row[k];  int nj = j + col[k];    int pathLength = dfs(mat visited ni nj x y);    // If a valid path is found from this direction  if (pathLength != -1)  {  maxPath = Math.Max(maxPath 1 + pathLength);  }  }    // Backtrack - unmark current cell  visited[i j] = false;    return maxPath;  }    static int FindLongestPath(int[] mat int xs int ys int xd int yd)  {  int m = mat.GetLength(0);  int n = mat.GetLength(1);    // Check if source or destination is blocked  if (mat[xs ys] == 0 || mat[xd yd] == 0)  {  return -1;  }    bool[] visited = new bool[m n];  return dfs(mat visited xs ys xd yd);  }    static void Main()  {  int[] mat = {  {1 1 1 1 1 1 1 1 1 1}  {1 1 0 1 1 0 1 1 0 1}  {1 1 1 1 1 1 1 1 1 1}  };    int xs = 0 ys = 0;   int xd = 1 yd = 7;     int result = FindLongestPath(mat xs ys xd yd);    if (result != -1)  Console.WriteLine(result);  else  Console.WriteLine(-1);  } }
JavaScript 
// Function to find the longest path using backtracking function dfs(mat visited i j x y) {  const m = mat.length;  const n = mat[0].length;    // If destination is reached  if (i === x && j === y) {  return 0;  }    // If cell is invalid blocked or already visited  if (i < 0 || i >= m || j < 0 || j >= n ||   mat[i][j] === 0 || visited[i][j]) {  return -1;   }    // Mark current cell as visited  visited[i][j] = true;    let maxPath = -1;    // Four possible moves: up down left right  const row = [-1 1 0 0];  const col = [0 0 -1 1];    for (let k = 0; k < 4; k++) {  const ni = i + row[k];  const nj = j + col[k];    const pathLength = dfs(mat visited   ni nj x y);    // If a valid path is found from this direction  if (pathLength !== -1) {  maxPath = Math.max(maxPath 1 + pathLength);  }  }    // Backtrack - unmark current cell  visited[i][j] = false;    return maxPath; } function findLongestPath(mat xs ys xd yd) {  const m = mat.length;  const n = mat[0].length;    // Check if source or destination is blocked  if (mat[xs][ys] === 0 || mat[xd][yd] === 0) {  return -1;  }    const visited = Array(m).fill().map(() => Array(n).fill(false));  return dfs(mat visited xs ys xd yd); }  const mat = [  [1 1 1 1 1 1 1 1 1 1]  [1 1 0 1 1 0 1 1 0 1]  [1 1 1 1 1 1 1 1 1 1]  ];    const xs = 0 ys = 0;   const xd = 1 yd = 7;     const result = findLongestPath(mat xs ys xd yd);    if (result !== -1)  console.log(result);  else  console.log(-1);

Produzione 
24

Complessità temporale: O(4^(m*n)) Per ogni cella nella matrice m x n l'algoritmo esplora fino a quattro possibili direzioni (su giù a sinistra a destra) che portano a un numero esponenziale di percorsi. Nel peggiore dei casi esplora tutti i possibili percorsi risultando in una complessità temporale di 4^(m*n).
Spazio ausiliario: O(m*n) L'algoritmo utilizza una matrice visitata m x n per tenere traccia delle celle visitate e uno stack di ricorsione che può crescere fino a una profondità di m * n nel caso peggiore (ad esempio quando si esplora un percorso che copre tutte le celle). Quindi lo spazio ausiliario è O(m*n).

[Approccio ottimizzato] Senza utilizzare spazio aggiuntivo

Invece di mantenere una matrice visitata separata, possiamo farlo riutilizzare la matrice di input per contrassegnare le celle visitate durante l'attraversamento. Ciò consente di risparmiare spazio aggiuntivo e garantisce comunque di non rivisitare la stessa cella in un percorso.



Di seguito è riportato l'approccio passo passo:

  1. Inizia dalla cella di origine(xs ys).
  2. Ad ogni passaggio esplora tutte e quattro le direzioni possibili (destra giù sinistra su).
  3. Per ogni mossa valida:
    • Controlla i confini e assicurati che la cella abbia valore1(cella libera).
    • Contrassegna la cella come visitata impostandola temporaneamente su0.
    • Passare alla cella successiva e incrementare la lunghezza del percorso.
  4. Se la cella di destinazione(xd yd)viene raggiunto confronta la lunghezza del percorso attuale con quella massima finora e aggiorna la risposta.
  5. Backtrack: ripristina il valore originale della cella (1) prima di ritornare per consentire ad altri sentieri di esplorarlo.
  6. Continua ad esplorare finché non vengono visitati tutti i percorsi possibili.
  7. Restituisce la lunghezza massima del percorso. Se la destinazione è irraggiungibile rientro-1
C++ 
#include    #include  #include  #include    using namespace std; // Function to find the longest path using backtracking without extra space int dfs(vector<vector<int>> &mat int i int j int x int y) {  int m = mat.size();  int n = mat[0].size();    // If destination is reached  if (i == x && j == y) {  return 0;  }    // If cell is invalid or blocked (0 means blocked or visited)  if (i < 0 || i >= m || j < 0 || j >= n || mat[i][j] == 0) {  return -1;   }    // Mark current cell as visited by temporarily setting it to 0  mat[i][j] = 0;    int maxPath = -1;    // Four possible moves: up down left right  int row[] = {-1 1 0 0};  int col[] = {0 0 -1 1};    for (int k = 0; k < 4; k++) {  int ni = i + row[k];  int nj = j + col[k];    int pathLength = dfs(mat ni nj x y);    // If a valid path is found from this direction  if (pathLength != -1) {  maxPath = max(maxPath 1 + pathLength);  }  }    // Backtrack - restore the cell's original value (1)  mat[i][j] = 1;    return maxPath; } int findLongestPath(vector<vector<int>> &mat int xs int ys int xd int yd) {  int m = mat.size();  int n = mat[0].size();    // Check if source or destination is blocked  if (mat[xs][ys] == 0 || mat[xd][yd] == 0) {  return -1;  }    return dfs(mat xs ys xd yd); } int main() {  vector<vector<int>> mat = {  {1 1 1 1 1 1 1 1 1 1}  {1 1 0 1 1 0 1 1 0 1}  {1 1 1 1 1 1 1 1 1 1}  };    int xs = 0 ys = 0;   int xd = 1 yd = 7;     int result = findLongestPath(mat xs ys xd yd);    if (result != -1)  cout << result << endl;  else  cout << -1 << endl;    return 0; }
Java 
public class GFG {    // Function to find the longest path using backtracking without extra space  public static int dfs(int[][] mat int i int j int x int y) {  int m = mat.length;  int n = mat[0].length;    // If destination is reached  if (i == x && j == y) {  return 0;  }    // If cell is invalid or blocked (0 means blocked or visited)  if (i < 0 || i >= m || j < 0 || j >= n || mat[i][j] == 0) {  return -1;   }    // Mark current cell as visited by temporarily setting it to 0  mat[i][j] = 0;    int maxPath = -1;    // Four possible moves: up down left right  int[] row = {-1 1 0 0};  int[] col = {0 0 -1 1};    for (int k = 0; k < 4; k++) {  int ni = i + row[k];  int nj = j + col[k];    int pathLength = dfs(mat ni nj x y);    // If a valid path is found from this direction  if (pathLength != -1) {  maxPath = Math.max(maxPath 1 + pathLength);  }  }    // Backtrack - restore the cell's original value (1)  mat[i][j] = 1;    return maxPath;  }    public static int findLongestPath(int[][] mat int xs int ys int xd int yd) {  int m = mat.length;  int n = mat[0].length;    // Check if source or destination is blocked  if (mat[xs][ys] == 0 || mat[xd][yd] == 0) {  return -1;  }    return dfs(mat xs ys xd yd);  }    public static void main(String[] args) {  int[][] mat = {  {1 1 1 1 1 1 1 1 1 1}  {1 1 0 1 1 0 1 1 0 1}  {1 1 1 1 1 1 1 1 1 1}  };    int xs = 0 ys = 0;   int xd = 1 yd = 7;     int result = findLongestPath(mat xs ys xd yd);    if (result != -1)  System.out.println(result);  else  System.out.println(-1);  } }
Python 
# Function to find the longest path using backtracking without extra space def dfs(mat i j x y): m = len(mat) n = len(mat[0]) # If destination is reached if i == x and j == y: return 0 # If cell is invalid or blocked (0 means blocked or visited) if i < 0 or i >= m or j < 0 or j >= n or mat[i][j] == 0: return -1 # Mark current cell as visited by temporarily setting it to 0 mat[i][j] = 0 maxPath = -1 # Four possible moves: up down left right row = [-1 1 0 0] col = [0 0 -1 1] for k in range(4): ni = i + row[k] nj = j + col[k] pathLength = dfs(mat ni nj x y) # If a valid path is found from this direction if pathLength != -1: maxPath = max(maxPath 1 + pathLength) # Backtrack - restore the cell's original value (1) mat[i][j] = 1 return maxPath def findLongestPath(mat xs ys xd yd): m = len(mat) n = len(mat[0]) # Check if source or destination is blocked if mat[xs][ys] == 0 or mat[xd][yd] == 0: return -1 return dfs(mat xs ys xd yd) def main(): mat = [ [1 1 1 1 1 1 1 1 1 1] [1 1 0 1 1 0 1 1 0 1] [1 1 1 1 1 1 1 1 1 1] ] xs ys = 0 0 xd yd = 1 7 result = findLongestPath(mat xs ys xd yd) if result != -1: print(result) else: print(-1) if __name__ == '__main__': main()
C# 
using System; class GFG {  // Function to find the longest path using backtracking without extra space  static int dfs(int[] mat int i int j int x int y)  {  int m = mat.GetLength(0);  int n = mat.GetLength(1);    // If destination is reached  if (i == x && j == y)  {  return 0;  }    // If cell is invalid or blocked (0 means blocked or visited)  if (i < 0 || i >= m || j < 0 || j >= n || mat[i j] == 0)  {  return -1;   }    // Mark current cell as visited by temporarily setting it to 0  mat[i j] = 0;    int maxPath = -1;    // Four possible moves: up down left right  int[] row = {-1 1 0 0};  int[] col = {0 0 -1 1};    for (int k = 0; k < 4; k++)  {  int ni = i + row[k];  int nj = j + col[k];    int pathLength = dfs(mat ni nj x y);    // If a valid path is found from this direction  if (pathLength != -1)  {  maxPath = Math.Max(maxPath 1 + pathLength);  }  }    // Backtrack - restore the cell's original value (1)  mat[i j] = 1;    return maxPath;  }    static int FindLongestPath(int[] mat int xs int ys int xd int yd)  {  // Check if source or destination is blocked  if (mat[xs ys] == 0 || mat[xd yd] == 0)  {  return -1;  }    return dfs(mat xs ys xd yd);  }    static void Main()  {  int[] mat = {  {1 1 1 1 1 1 1 1 1 1}  {1 1 0 1 1 0 1 1 0 1}  {1 1 1 1 1 1 1 1 1 1}  };    int xs = 0 ys = 0;   int xd = 1 yd = 7;     int result = FindLongestPath(mat xs ys xd yd);    if (result != -1)  Console.WriteLine(result);  else  Console.WriteLine(-1);  } }
JavaScript 
// Function to find the longest path using backtracking without extra space function dfs(mat i j x y) {  const m = mat.length;  const n = mat[0].length;    // If destination is reached  if (i === x && j === y) {  return 0;  }    // If cell is invalid or blocked (0 means blocked or visited)  if (i < 0 || i >= m || j < 0 || j >= n || mat[i][j] === 0) {  return -1;   }    // Mark current cell as visited by temporarily setting it to 0  mat[i][j] = 0;    let maxPath = -1;    // Four possible moves: up down left right  const row = [-1 1 0 0];  const col = [0 0 -1 1];    for (let k = 0; k < 4; k++) {  const ni = i + row[k];  const nj = j + col[k];    const pathLength = dfs(mat ni nj x y);    // If a valid path is found from this direction  if (pathLength !== -1) {  maxPath = Math.max(maxPath 1 + pathLength);  }  }    // Backtrack - restore the cell's original value (1)  mat[i][j] = 1;    return maxPath; } function findLongestPath(mat xs ys xd yd) {  const m = mat.length;  const n = mat[0].length;    // Check if source or destination is blocked  if (mat[xs][ys] === 0 || mat[xd][yd] === 0) {  return -1;  }    return dfs(mat xs ys xd yd); }  const mat = [  [1 1 1 1 1 1 1 1 1 1]  [1 1 0 1 1 0 1 1 0 1]  [1 1 1 1 1 1 1 1 1 1]  ];    const xs = 0 ys = 0;   const xd = 1 yd = 7;     const result = findLongestPath(mat xs ys xd yd);    if (result !== -1)  console.log(result);  else  console.log(-1);

Produzione 
24

Complessità temporale: O(4^(m*n))L'algoritmo esplora ancora fino a quattro direzioni per cella nella matrice m x n risultando in un numero esponenziale di percorsi. La modifica sul posto non influisce sul numero di percorsi esplorati, quindi la complessità temporale rimane 4^(m*n).
Spazio ausiliario: O(m*n) Mentre la matrice visitata viene eliminata modificando la matrice di input sul posto, lo stack di ricorsione richiede ancora spazio O(m*n) poiché la profondità di ricorsione massima può essere m * n nel caso peggiore (ad esempio un percorso che visita tutte le celle in una griglia con principalmente 1).

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