Permutation Coefficient using dynamic programming

Permutation refers to the process of arranging all the members of a given set to form a sequence. The number of permutations on a set of n elements is given by n! , where “!” represents factorial.

The Permutation Coefficient represented by P(n, k) is used to represent the number of ways to obtain an ordered subset having k elements from a set of n elements.

Examples :

P(10, 2) = 90 P(10, 3) = 720 P(10, 0) = 1 P(10, 1) = 10

The coefficient can also be computed recursively using the below recursive formula:

P(n, k) = P(n-1, k) + k* P(n-1, k-1)

If we observe closely, we can analyze that the problem has overlapping substructure, hence we can apply dynamic programming here.
Below is a program implementing the same idea.

// A Dynamic Programming based

// solution that uses table P[][]

// to calculate the Permutation

// Coefficient

#include<bits/stdc++.h>

// Returns value of Permutation

// Coefficient P(n, k)

int permutationCoeff( int n, int k)

{

`` int P[n + 1][k + 1];

`` // Calculate value of Permutation

`` // Coefficient in bottom up manner

`` for ( int i = 0; i <= n; i++)

`` {

`` for ( int j = 0; j <= std::min(i, k); j++)

`` {

`` // Base Cases

`` if (j == 0)

`` P[i][j] = 1;

`` // Calculate value using

`` // previosly stored values

`` else

`` P[i][j] = P[i - 1][j] +

`` (j * P[i - 1][j - 1]);

`` // This step is important

`` // as P(i,j)=0 for j>i

`` P[i][j + 1] = 0;

`` }

`` }

`` return P[n][k];

}

// Driver Code

int main()

{

`` int n = 10, k = 2;

`` printf ( "Value of P(%d, %d) is %d " ,

`` n, k, permutationCoeff(n, k));

`` return 0;

}

Output :

Value of P(10, 2) is 90

Here as we can see the time complexity is O(nk) and space complexity is O(nk) as the program uses an auxiliary matrix to store the result.

Can we do it in O(n) time ?
Let us suppose we maintain a single 1D array to compute the factorials up to n. We can use computed factorial value and apply the formula P(n, k) = n! / (n-k)!. Below is a program illustrating the same concept.

// A O(n) solution that uses

// table fact[] to calculate

// the Permutation Coefficient

#include<bits/stdc++.h>

using namespace std;

// Returns value of Permutation

// Coefficient P(n, k)

int permutationCoeff( int n, int k)

{

`` int fact[n + 1];

`` // Base case

`` fact[0] = 1;

`` // Calculate value

`` // factorials up to n

`` for ( int i = 1; i <= n; i++)

`` fact[i] = i * fact[i - 1];

`` // P(n,k) = n! / (n - k)!

`` return fact[n] / fact[n - k];

}

// Driver Code

int main()

{

`` int n = 10, k = 2;

``

`` cout << "Value of P(" << n << ", "

`` << k << ") is "

`` << permutationCoeff(n, k);

`` return 0;

}

Output :

Value of P(10, 2) is 90

A O(n) time and O(1) Extra Space Solution

// A O(n) time and O(1) extra

// space solution to calculate

// the Permutation Coefficient

#include <iostream>

using namespace std;

int PermutationCoeff( int n, int k)

{

`` int P = 1;

`` // Compute n*(n-1)*(n-2)....(n-k+1)

`` for ( int i = 0; i < k; i++)

`` P *= (n-i) ;

`` return P;

}

// Driver Code

int main()

{

`` int n = 10, k = 2;

`` cout << "Value of P(" << n << ", " << k

`` << ") is " << PermutationCoeff(n, k);

`` return 0;

}

Output :

Value of P(10, 2) is 90