Start by understanding why the naive DP approach for TSP has a time complexity of O(n² * 2ⁿ) by breaking down the state transitions and the role of the bitmask.

Recognize that the bitmask represents subsets of visited cities, and the DP state `dp[mask][i]` stores the minimum cost to reach city `i` with the set of visited cities represented by `mask`.

To optimize the given O(n² * 2ⁿ) solution, focus on reducing the state space or transitions—consider whether all subsets of size `k` need to be explicitly computed or if symmetry can be exploited.