Breadth First Search on Matrix in C++

C++Server Side ProgrammingProgramming

In a given matrix, there are four objects to analyze the element position: left, right, bottom and top.

Breadth First Search is nothing but finding the shortest distance between the two elements of a given 2-D Matrix. Thus in each cell, there are four operations we can perform which can be expressed in four numerals such as,

  • '2' describes that the cell in the matrix is Source.
  • '3' describes that the cell in the matrix is Destination.
  • '1' describes that the cell can be moved further in a direction.
  • '0' describes that the cell in the matrix can not be moved in any direction.

On the basis of adobe justification, we can perform a Breadth First Search Operation on a given Matrix.

Approach to Solve this Problem

The algorithm to traverse the whole matrix and find the minimum or shortest distance between any cell using BFS is as follows:

  • First take the input row and column.
  • Initialize a matrix with the given row and column.
  • An integer function shortestDist(int row, int col, int mat[][col]) takes the row, column and matrix as the input and returns the shortest distance between the elements of the matrix.
  • Initialize the variable source and destination to find out the source as well as the destination element.
  • If the element is '3', then mark it as the destination and if the element is '2', then mark it as the source element.
  • Now initialize the queue data structure to implement Breadth First Search on the given matrix.
  • Insert the row and column of the matrix in the queue as pairs. Now move in the cell and find out if it is a destination cell or not. If the destination cell is having a distance minimum or less than the current cell, then update the distance.
  • Again move to another direction to find out the minimum distance of the cell from the current cell.
  • Return the minimum distance as the output.

Example

#include<bits/stdc++.h>
using namespace std;
int findDistance(int row, int col, int mat[][5]) {
   int source_i, source_j, destination_i, destination_j;
   for (int i = 0; i < row; i++) {
      for (int j = 0; j < col; j++) {
         if (mat[i][j] == 2) {
            source_i = i;
            source_j = j;
         }
         if (mat[i][j] == 3) {
            destination_i = i;
            destination_j = j;
         }
      }
   }
   int dist[row][col];
   for (int i = 0; i < row; i++) {
      for (int j = 0; j < col; j++)
         dist[i][j] = INT_MAX;
   }
   // initialise queue to start BFS on matrix
   queue < pair < int, int >> q;
   q.push(make_pair(source_i, source_j));
   dist[source_i][source_j] = 0;

   // modified BFS by add constraint checks
   while (!q.empty()) {
      // storing the x co-ordinate or row information of cell
      int x = q.front().first;
      // storing the y co-ordinate or column information of cell
      int y = q.front().second;
      // Remove the cell from queue
      q.pop();

      // If move towards left is allowed or it is the destnation cell
      if (y - 1 >= 0 && (mat[x][y - 1] == 1 || mat[x][y - 1] == 3)) {
         // if distance to reach the cell to the left is less than the computed previous path distance, update it
         if (dist[x][y] + 1 < dist[x][y - 1]) {
            dist[x][y - 1] = dist[x][y] + 1;
            q.push(mkp(x, y - 1));
         }
      }
      // If move towards right is allowed or it is the destination cell
      if (y + 1 < col && (mat[x][y + 1] == 1 || mat[x][y + 1] == 3)) {
         // if distance to reach the cell to the right is less than the computed previous path distance, update it
         if (dist[x][y] + 1 < dist[x][y + 1]) {
            dist[x][y + 1] = dist[x][y] + 1;
            q.push(mkp(x, y + 1));
         }
      }
      // If upward direction is allowed
      if (x - 1 >= 0 && (mat[x - 1][y] == 1 || mat[x - 1][y] == 3)) {
         if (dist[x][y] + 1 < dist[x - 1][y]) {
            dist[x - 1][y] = dist[x][y] + 1;
            q.push(mkp(x - 1, y));
         }
      }

      // If downward direction allowed
      if (x + 1 < row && (mat[x + 1][y] == 1 || mat[x + 1][y] == 3)) {
         // if distance to reach the cell to the down is less than the computed previous path distance, update it
         if (dist[x][y] + 1 < dist[x + 1][y]) {
            dist[x + 1][y] = dist[x][y] + 1;
            q.push(mkp(x + 1, y));
         }
      }
   }
   return dist[destination_i][destination_j];
}

int main() {
   // initialising number of rows and columns
   int row = 5;
   int col = 5;
   // initialising matrix
   int mat[][5] = {
      {1, 0, 0, 2, 1},
      {1, 0, 1, 1, 1},
      {0, 1, 1, 2, 0},
      {3, 1, 0, 0, 1},
      {1, 1, 0, 0, 1}
   };
   int answer = findDistance(row, col, mat);
   // When source and destination are unreachable
   if (answer == INT_MAX)
      cout << "No Path Found" << endl;
   else {
      cout << "The Shortest Distance between Source and Destination is:" << endl;
      cout << answer << endl;
   }
   return 0;
}

Output

The Shortest Distance between Source and Destination is:4
raja
Published on 23-Feb-2021 04:46:33
Advertisements