Check if it is possible to reach a number by making jumps of two given length
Given a starting position ‘k’ and two jump sizes ‘d1’ and ‘d2’, our task is to find the minimum number of jumps needed to reach ‘x’ if it is possible.
At any position P, we are allowed to jump to positions :
- P + d1 and P – d1
- P + d2 and P – d2
Examples:
Input : k = 10, d1 = 4, d2 = 6 and x = 8 Output : 2 1st step 10 + d1 = 14 2nd step 14 - d2 = 8 Input : k = 10, d1 = 4, d2 = 6 and x = 9 Output : -1 -1 indicates it is not possible to reach x.
In the previous article we discussed a strategy to check whether a list of numbers is reachable by K by making jump of two given lengths.
Here, instead of a list of numbers, we are given a single integer x and if it is reachable from k then the task is to find the minimum number of steps or jumps needed.
We will solve this using Breadth first Search:
Approach:
- Check if ‘x’ is reachable from k. The number x is reachable from k if it satisfies (x – k) % gcd(d1, d2) = 0.
- If x is reachable :
- Maintain a hash table to store the already visited positions.
- Apply bfs algorithm starting from position k.
- If you reach position P in ‘stp’ steps, you can reach p+d1 position in ‘stp+1’ steps.
- If position P is the required position ‘x’ then steps taken to reach P is the answer
The image below depicts how the algorithm finds out number of steps needed to reach x = 8 with k = 10, d1 = 4 and d2 = 6.
Below is the implementation of the above approach:
C++
#include <bits/stdc++.h> using namespace std; // Function to perform BFS traversal to // find minimum number of step needed // to reach x from K int minStepsNeeded( int k, int d1, int d2, int x) { // Calculate GCD of d1 and d2 int gcd = __gcd(d1, d2); // If position is not reachable // return -1 if ((k - x) % gcd != 0) return -1; // Queue for BFS queue<pair< int , int > > q; // Hash Table for marking // visited positions unordered_set< int > visited; // we need 0 steps to reach K q.push({ k, 0 }); // Mark starting position // as visited visited.insert(k); while (!q.empty()) { int s = q.front().first; // stp is the number of steps // to reach position s int stp = q.front().second; if (s == x) return stp; q.pop(); if (visited.find(s + d1) == visited.end()) { // if position not visited // add to queue and mark visited q.push({ s + d1, stp + 1 }); visited.insert(s + d1); } if (visited.find(s + d2) == visited.end()) { q.push({ s + d2, stp + 1 }); visited.insert(s + d2); } if (visited.find(s - d1) == visited.end()) { q.push({ s - d1, stp + 1 }); visited.insert(s - d1); } if (visited.find(s - d2) == visited.end()) { q.push({ s - d2, stp + 1 }); visited.insert(s - d2); } } } // Driver Code int main() { int k = 10, d1 = 4, d2 = 6, x = 8; cout << minStepsNeeded(k, d1, d2, x); return 0; } |
Java
// Java implementation of the approach import java.util.*; class GFG { static class pair { int first, second; public pair( int first, int second) { this .first = first; this .second = second; } } static int __gcd( int a, int b) { if (b == 0 ) return a; return __gcd(b, a % b); } // Function to perform BFS traversal to // find minimum number of step needed // to reach x from K static int minStepsNeeded( int k, int d1, int d2, int x) { // Calculate GCD of d1 and d2 int gcd = __gcd(d1, d2); // If position is not reachable // return -1 if ((k - x) % gcd != 0 ) return - 1 ; // Queue for BFS Queue<pair> q = new LinkedList<>(); // Hash Table for marking // visited positions HashSet<Integer> visited = new HashSet<>(); // we need 0 steps to reach K q.add( new pair(k, 0 )); // Mark starting position // as visited visited.add(k); while (!q.isEmpty()) { int s = q.peek().first; // stp is the number of steps // to reach position s int stp = q.peek().second; if (s == x) return stp; q.remove(); if (!visited.contains(s + d1)) { // if position not visited // add to queue and mark visited q.add( new pair(s + d1, stp + 1 )); visited.add(s + d1); } if (visited.contains(s + d2)) { q.add( new pair(s + d2, stp + 1 )); visited.add(s + d2); } if (!visited.contains(s - d1)) { q.add( new pair(s - d1, stp + 1 )); visited.add(s - d1); } if (!visited.contains(s - d2)) { q.add( new pair(s - d2, stp + 1 )); visited.add(s - d2); } } return Integer.MIN_VALUE; } // Driver Code public static void main(String[] args) { int k = 10 , d1 = 4 , d2 = 6 , x = 8 ; System.out.println(minStepsNeeded(k, d1, d2, x)); } } // This code is contributed by 29AjayKumar |
Python3
# Python3 implementation of the approach from math import gcd as __gcd from collections import deque as queue # Function to perform BFS traversal to # find minimum number of step needed # to reach x from K def minStepsNeeded(k, d1, d2, x): # Calculate GCD of d1 and d2 gcd = __gcd(d1, d2) # If position is not reachable # return -1 if ((k - x) % gcd ! = 0 ): return - 1 # Queue for BFS q = queue() # Hash Table for marking # visited positions visited = dict () # we need 0 steps to reach K q.appendleft([k, 0 ]) # Mark starting position # as visited visited[k] = 1 while ( len (q) > 0 ): sr = q.pop() s, stp = sr[ 0 ], sr[ 1 ] # stp is the number of steps # to reach position s if (s = = x): return stp if (s + d1 not in visited): # if position not visited # add to queue and mark visited q.appendleft([(s + d1), stp + 1 ]) visited[(s + d1)] = 1 if (s + d2 not in visited): q.appendleft([(s + d2), stp + 1 ]) visited[(s + d2)] = 1 if (s - d1 not in visited): q.appendleft([(s - d1), stp + 1 ]) visited[(s - d1)] = 1 if (s - d2 not in visited): q.appendleft([(s - d2), stp + 1 ]) visited[(s - d2)] = 1 # Driver Code k = 10 d1 = 4 d2 = 6 x = 8 print (minStepsNeeded(k, d1, d2, x)) # This code is contributed by Mohit Kumar |
C#
// C# implementation of the approach using System; using System.Collections.Generic; class GFG { public class pair { public int first, second; public pair( int first, int second) { this .first = first; this .second = second; } } static int __gcd( int a, int b) { if (b == 0) return a; return __gcd(b, a % b); } // Function to perform BFS traversal to // find minimum number of step needed // to reach x from K static int minStepsNeeded( int k, int d1, int d2, int x) { // Calculate GCD of d1 and d2 int gcd = __gcd(d1, d2); // If position is not reachable // return -1 if ((k - x) % gcd != 0) return -1; // Queue for BFS Queue<pair> q = new Queue<pair>(); // Hash Table for marking // visited positions HashSet< int > visited = new HashSet< int >(); // we need 0 steps to reach K q.Enqueue( new pair(k, 0)); // Mark starting position // as visited visited.Add(k); while (q.Count != 0) { int s = q.Peek().first; // stp is the number of steps // to reach position s int stp = q.Peek().second; if (s == x) return stp; q.Dequeue(); if (!visited.Contains(s + d1)) { // if position not visited // add to queue and mark visited q.Enqueue( new pair(s + d1, stp + 1)); visited.Add(s + d1); } if (!visited.Contains(s + d2)) { q.Enqueue( new pair(s + d2, stp + 1)); visited.Add(s + d2); } if (!visited.Contains(s - d1)) { q.Enqueue( new pair(s - d1, stp + 1)); visited.Add(s - d1); } if (!visited.Contains(s - d2)) { q.Enqueue( new pair(s - d2, stp + 1)); visited.Add(s - d2); } } return int .MinValue; } // Driver Code public static void Main(String[] args) { int k = 10, d1 = 4, d2 = 6, x = 8; Console.WriteLine(minStepsNeeded(k, d1, d2, x)); } } // This code is contributed by PrinciRaj1992 |
Javascript
<script> // JavaScript implementation of the approach function __gcd(a,b) { if (b == 0) return a; return __gcd(b, a % b); } // Function to perform BFS traversal to // find minimum number of step needed // to reach x from K function minStepsNeeded(k,d1,d2,x) { // Calculate GCD of d1 and d2 let gcd = __gcd(d1, d2); // If position is not reachable // return -1 if ((k - x) % gcd != 0) return -1; // Queue for BFS let q = []; // Hash Table for marking // visited positions let visited = new Set(); // we need 0 steps to reach K q.push([k, 0 ]); // Mark starting position // as visited visited.add(k); while (q.length!=0) { let s = q[0][0]; // stp is the number of steps // to reach position s let stp = q[0][1]; if (s == x) return stp; q.shift(); if (!visited.has(s + d1)) { // if position not visited // add to queue and mark visited q.push([s + d1, stp + 1]); visited.add(s + d1); } if (!visited.has(s + d2)) { q.push([s + d2, stp + 1]); visited.add(s + d2); } if (!visited.has(s - d1)) { q.push([s - d1, stp + 1]); visited.add(s - d1); } if (!visited.has(s - d2)) { q.push([s - d2, stp + 1]); visited.add(s - d2); } } return Number.MIN_VALUE; } // Driver Code let k = 10, d1 = 4, d2 = 6, x = 8; document.write(minStepsNeeded(k, d1, d2, x)); // This code is contributed by patel2127 </script> |
2
Complexity Analysis:
- Time Complexity: O(|k-x|)
- Auxiliary Space: O(|k-x|)
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