Decrease strikes to segregate even and odd by swapping adjoining components

Given an array arr[] of measurement N, the duty is to search out the minimal strikes to segregate even and odd numbers by swapping two adjoining components at a time.

Instance:

Enter: N = 7, arr = {3, 5, 2, 7, 9, 11, 12}
Output: 3
Rationalization: Swap arr[2] and arr[3] to get arr = {3, 5, 7, 2, 9, 11, 12}.
Transfer 2: Swap arr[3] and arr[4] to get arr = {3, 5, 7, 9, 2, 11, 12}.
Transfer 3: Swap arr[4] and arr[5] to get arr = {3, 5, 7, 9, 11, 2, 12}.
All odds are originally from arr[0 . . . 4] 
and evens on the finish from arr[5 . . . 6].

Enter: N = 5, arr = {3, 5, 7, 2, 4}
Output: 0

Strategy:

This drawback could be damaged down into two sub-problems: 

• Shifting all odd to the entrance or 
• shifting all odd to the tip (minimal of which can give us the optimum reply). 

So this drawback could be solved utilizing the grasping strategy, the place initially the variety of strikes to shift odd to the begining are counted after which the variety of strikes to shift odd to the tip are counted and minimal of each is returned as reply.

To shift any quantity by consecutive swapping, strikes required is abs(j – i) the place j is the index of the final variety of the other parity and i is the index of the present quantity. 

Observe the given steps to resolve the issue:

• Traverse the array arr from 0 to n-1 (say i).
  • If arr[i] is odd then add i-j in startMoves and increment j.
  • Reinitialize j to n-1.
• Traverse the array arr from n-1 to 0 (say i).
  • If arr[i] is odd then add j-i to endMoves and decrement j.
• Return minimal of startMoves and endMoves as the ultimate reply.

Beneath is the implementation of this strategy:

Time Complexity: O(N)
Auxiliary Area: O(1)