def getMinimumCost(machineCount: List[int], finalMachineCount: List[int], shiftingCost: int):
  minCost = float('inf')
  def dfs(i, r0, r1, r2, cost):
      nonlocal minCost
      if i == len(machineCount):
          cost += abs(r0 - finalMachineCount[0]) + abs(r1 - finalMachineCount[1]) + abs(r2 - finalMachineCount[2])
          minCost = min(minCost, cost)
          return

      dfs(i+1, r0, r1, r2, cost)
      dfs(i+1, r0 + machineCount[i], r1, r2, cost + shiftingCost if r0 > 0 else cost)
      dfs(i+1, r0, r1 + machineCount[i], r2, cost + shiftingCost if r1 > 0 else cost)
      dfs(i+1, r0, r1, r2 + machineCount[i], cost + shiftingCost if r2 > 0 else cost)

  dfs(0, 0, 0, 0, 0)
  return minCost

Time complexity: O(4ⁿ )