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Solution: Minimize Manhattan Distances

Understand how to reduce the maximum Manhattan distance between points on a 2D plane by removing one point. Explore the role of coordinate sums and differences, and learn a method that efficiently identifies candidate points impacting the distance extrema, ensuring an optimal solution with linear time complexity.

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 ...