Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH scholarly article en Dey, Sanjana; Foucaud, Florent; Nandy, Subhas C.; Sen, Arunabha https://www.dagstuhl.de/lipics License: Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)
when quoting this document, please refer to the following
DOI:
URN: urn:nbn:de:0030-drops-133686
URL:

; ; ;

Discriminating Codes in Geometric Setups

pdf-format:


Abstract

We study two geometric variations of the discriminating code problem. In the discrete version, a finite set of points P and a finite set of objects S are given in ℝ^d. The objective is to choose a subset S^* ⊆ S of minimum cardinality such that the subsets S_i^* ⊆ S^* covering p_i, satisfy S_i^* ≠ ∅ for each i = 1,2,…, n, and S_i^* ≠ S_j^* for each pair (i,j), i ≠ j. In the continuous version, the solution set S^* can be chosen freely among a (potentially infinite) class of allowed geometric objects.
In the 1-dimensional case (d = 1), the points are placed on some fixed-line L, and the objects in S are finite segments of L (called intervals). We show that the discrete version of this problem is NP-complete. This is somewhat surprising as the continuous version is known to be polynomial-time solvable. This is also in contrast with most geometric covering problems, which are usually polynomial-time solvable in 1D.
We then design a polynomial-time 2-approximation algorithm for the 1-dimensional discrete case. We also design a PTAS for both discrete and continuous cases when the intervals are all required to have the same length.
We then study the 2-dimensional case (d = 2) for axis-parallel unit square objects. We show that both continuous and discrete versions are NP-hard, and design polynomial-time approximation algorithms with factors 4+ε and 32+ε, respectively (for every fixed ε > 0).

BibTeX - Entry

@InProceedings{dey_et_al:LIPIcs:2020:13368,
  author =	{Sanjana Dey and Florent Foucaud and Subhas C. Nandy and Arunabha Sen},
  title =	{{Discriminating Codes in Geometric Setups}},
  booktitle =	{31st International Symposium on Algorithms and Computation (ISAAC 2020)},
  pages =	{24:1--24:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-173-3},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{181},
  editor =	{Yixin Cao and Siu-Wing Cheng and Minming Li},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/13368},
  URN =		{urn:nbn:de:0030-drops-133686},
  doi =		{10.4230/LIPIcs.ISAAC.2020.24},
  annote =	{Keywords: Discriminating code, Approximation algorithm, Segment stabbing, Geometric Hitting set}
}

Keywords: Discriminating code, Approximation algorithm, Segment stabbing, Geometric Hitting set
Seminar: 31st International Symposium on Algorithms and Computation (ISAAC 2020)
Issue date: 2020
Date of publication: 04.12.2020


DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI