Search⌘ K
AI Features

Solution: Minimize Manhattan Distances

Explore how to minimize the maximum Manhattan distance between points on a 2D plane by strategically removing one point. Understand how coordinate sums and differences determine distances and identify optimal removals to reduce the maximum distance while maintaining an efficient linear time solution.

Statement

You are given an array, points, where each element in points[i] =[xj,yi]= [x_j, y_i] represents the integer coordinates of a point in a 2D plane. The distance between any two points is defined as the Manhattan distanceThe Manhattan distance between two cells (x1, y1) and (x2, y2) is |x_1 - x_2| + |y_1 - y_2|..

Your task is to determine and return the smallest possible value for the maximum distance between any two points after removing exactly one point from the array.

Constraints:

  • 33 \leq points.length 103\leq 10^3 ...