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Algorithms for k-Dispersion for Points in Convex Position in the Plane

  • Birla Institute of Technology and Science Pilani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In this paper, we consider the following k-dispersion problem. Given a set S of n points placed in the plane in convex position and an integer k (0 < k< n ), the objective is to compute a subset S⊂ S such that | S| = k and the minimum distance between a pair of points in S is maximized. Based on the bounded search tree method, we propose an exact fixed-parameter algorithm in O(2 kn2log 2n) time for this problem, where k is the parameter. The proposed exact algorithm improves on the algorithm of Akagi et al. (2018), which requires time nO(k), whenever k< clog 2n for some constant c. We then give an exact polynomial-time (O(n4k2) ) algorithm, for any k> 0, thus answering the open question about the complexity of this restricted dispersion problem. For k= 3, there is an O(n2) -time algorithm by Kobayashi et al. (2021).

Original languageEnglish
Title of host publicationAlgorithms and Discrete Applied Mathematics - 9th International Conference, CALDAM 2023, Proceedings
EditorsAmitabha Bagchi, Rahul Muthu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages59-70
Number of pages12
ISBN (Print)9783031252105
DOIs
StatePublished - 2023
Event9th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2023 - Gandhinagar, India
Duration: Feb 9 2023Feb 11 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13947 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2023
Country/TerritoryIndia
CityGandhinagar
Period02/9/2302/11/23

Keywords

  • Delaunay triangulation
  • Dynamic programming
  • Fixed parameter tractable
  • Max-min dispersion
  • Obnoxious facility location

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