Maximize the Distance Between Points on a Square

Pick k given points that lie on a square's boundary to maximize the minimum pairwise Manhattan distance among the chosen points. The algorithmic challenge is to decide the largest d such that you can select k points with pairwise Manhattan distance ≥ d — typically addressed by binary-searching d with a feasibility check that leverages the boundary geometry and the small k (≤25) vs potentially large point set.