Question

I am trying to solve the Knight Tour problem using bactracking as given on this site.

Implementation given on the site takes about 0.49 seconds on ideone.

int solveKTUtil(int x, int y, int movei, int sol[N][N], int xMove[N],
                int yMove[N])
{
   int k, next_x, next_y;
   if (movei == N*N)
       return true;

   /* Try all next moves from the current coordinate x, y */
   for (k = 0; k < 8; k++)
   {
       next_x = x + xMove[k];
       next_y = y + yMove[k];
       if (isSafe(next_x, next_y, sol))
       {
         sol[next_x][next_y] = movei;
         if (solveKTUtil(next_x, next_y, movei+1, sol, xMove, yMove) == true)
             return true;
         else
             sol[next_x][next_y] = -1;// backtracking
       }
   }

   return false;
}

while one implemented by me which is almost same is showing time limit exceeded(more than 5 seconds) on ideone.

int generateMoves(int x, int y, int moveNum, int soln[][N], int xMoves[], int yMoves[])//making move number 'moveNum' from x and y.
{
        if(moveNum == N*N){
                return 1;
        }
        else{
                int i, nextX, nextY;
                for(i=0; i<8; ++i){
                        nextX = x + xMoves[i];
                        nextY = y + yMoves[i];

                        if(isSafe(nextX, nextY, soln)){
                                soln[nextX][nextY] = moveNum;
                                if( generateMoves(nextX, nextY, moveNum+1, soln, xMoves, yMoves) ){
                                        return 1;
                                }
                                else{
                                        soln[nextX][nextY] = -1;
                                }
                        }
                }
                return 0;
        }
}

what is executing for so long in my code?

Answer 1

Changing xMoves/yMoves seems to work: ideone. It could just be the search order causing it to find a solution earlier.

There are too many possible 63, 62, 61 etc length tours that can’t reach the final remaining squares. A brute-force search would have to go through all of them in the worst-case. The algorithm that worked just got lucky by trying a sequence of moves that led to a solution early.