Count of permutations of an Array having each element as a multiple or a factor of its index

Given an integer, N, the task is to count the number of ways to generate an array, arr[] of consisting of N integers such that for every index i(1-based indexing), arr[i] is either a factor or a multiple of i, or both. The arr[] must be the permutations of all the numbers from the range [1, N].

Examples:

Input: N=2
Output: 2
Explanation:
Two possible arrangements are {1, 2} and {2, 1}
Input: N=3
Output: 3
Explanation:
The 6 possible arrangements are {1, 2, 3}, {2, 1, 3}, {3, 2, 1}, {3, 1, 2}, {2, 3, 1} and {1, 3, 2}.
Among them, the valid arrangements are {1, 2, 3}, {2, 1, 3} and {3, 2, 1}.

Approach: The problem can be solved using Backtracking technique and the concept of print all permutations using recursion. Follow the steps below to find the recurrence relation:

  1. Traverse the range [1, N].
  2. For the current index pos, if i % pos == 0 and i % pos == 0, then insert i into the arrangement and use the concept of Backtracking to find valid permutations.
  3. Remove i.
  4. Repeat the above steps for all values in the range [1, N] and finally, print the count of valid permutations.

Below is the implementation of the above approach:
 



C++

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// C++ Program to implement
// the above approach
#include <bits/stdc++.h>
using namespace std;
 
// Function to find the count of
// desired permutations
int findPermutation(unordered_set<int>& arr,
                    int N)
{
    int pos = arr.size() + 1;
 
    // Base case
    if (pos > N)
        return 1;
 
    int res = 0;
 
    for (int i = 1; i <= N; i++) {
 
        // If i has not been inserted
        if (arr.find(i) == arr.end()) {
 
            // Backtrack
            if (i % pos == 0 or pos % i == 0) {
 
                // Insert i
                arr.insert(i);
 
                // Recur to find valid permutations
                res += findPermutation(arr, N);
 
                // Remove i
                arr.erase(arr.find(i));
            }
        }
    }
 
    // Return the final count
    return res;
}
 
// Driver Code
int main()
{
    int N = 5;
    unordered_set<int> arr;
    cout << findPermutation(arr, N);
 
    return 0;
}

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Java

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// Java program to implement
// the above approach
import java.util.*;
 
class GFG{
     
// Function to find the count of
// desired permutations
static int findPermutation(Set<Integer>arr,
                           int N)
{
    int pos = arr.size() + 1;
 
    // Base case
    if (pos > N)
        return 1;
 
    int res = 0;
 
    for(int i = 1; i <= N; i++)
    {
         
        // If i has not been inserted
        if (! arr.contains(i))
        {
             
            // Backtrack
            if (i % pos == 0 || pos % i == 0)
            {
                 
                // Insert i
                arr.add(i);
 
                // Recur to find valid permutations
                res += findPermutation(arr, N);
 
                // Remove i
                arr.remove(i);
            }
        }
    }
 
    // Return the final count
    return res;
}
 
// Driver Code
public static void main(String []args)
{
    int N = 5;
    Set<Integer> arr = new HashSet<Integer>();
     
    System.out.print(findPermutation(arr, N));
}
}
 
// This code is contributed by chitranayal

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Python3

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# Python3 program to implement
# the above approach
 
# Function to find the count of
# desired permutations
def findPermutation(arr, N):
 
    pos = len(arr) + 1
 
    # Base case
    if(pos > N):
        return 1
 
    res = 0
 
    for i in range(1, N + 1):
 
        # If i has not been inserted
        if(i not in arr):
 
            # Backtrack
            if(i % pos == 0 or pos % i == 0):
 
                # Insert i
                arr.add(i)
 
                # Recur to find valid permutations
                res += findPermutation(arr, N)
 
                # Remove i
                arr.remove(i)
 
    # Return the final count
    return res
 
# Driver Code
N = 5
arr = set()
 
# Function call
print(findPermutation(arr, N))
 
# This code is contributed by Shivam Singh

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C#

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// C# program to implement
// the above approach
using System;
using System.Collections.Generic;
 
class GFG{
     
// Function to find the count of
// desired permutations
static int findPermutation(HashSet<int>arr,
                           int N)
{
    int pos = arr.Count + 1;
 
    // Base case
    if (pos > N)
        return 1;
 
    int res = 0;
 
    for(int i = 1; i <= N; i++)
    {
         
        // If i has not been inserted
        if (! arr.Contains(i))
        {
             
            // Backtrack
            if (i % pos == 0 || pos % i == 0)
            {
                 
                // Insert i
                arr.Add(i);
 
                // Recur to find valid permutations
                res += findPermutation(arr, N);
 
                // Remove i
                arr.Remove(i);
            }
        }
    }
 
    // Return the readonly count
    return res;
}
 
// Driver Code
public static void Main(String []args)
{
    int N = 5;
    HashSet<int> arr = new HashSet<int>();
     
    Console.Write(findPermutation(arr, N));
}
}
 
// This code is contributed by gauravrajput1

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Output: 

10



 

Time Complexity: O(N×N!)
Auxiliary Space: O(N)
 

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Improved By : chitranayal, GauravRajput1