Optimum Partition Parameter of Divide-and-Conquer Algorithm for Solving Closest-Pair Problem

TL;DR

This paper investigates how partitioning the problem space into more than two parts in divide-and-conquer algorithms can improve performance in solving the closest pair problem.

Contribution

It proposes a novel approach of dividing the problem into n parts, potentially enhancing efficiency over traditional binary partitioning methods.

Findings

Partitioning into more than two parts can improve algorithm performance.

The proposed method offers a new perspective on problem space division.

Experimental results suggest potential efficiency gains.

Abstract

Divide and Conquer is a well known algorithmic procedure for solving many kinds of problem. In this procedure, the problem is partitioned into two parts until the problem is trivially solvable. Finding the distance of the closest pair is an interesting topic in computer science. With divide and conquer algorithm we can solve closest pair problem. Here also the problem is partitioned into two parts until the problem is trivially solvable. But it is theoretically and practically observed that sometimes partitioning the problem space into more than two parts can give better performances. In this paper, a new proposal is given that dividing the problem space into (n) number of parts can give better result while divide and conquer algorithm is used for solving the closest pair of point's problem.