A PTAS for the Horizontal Rectangle Stabbing Problem

Arindam Khan, Aditya Subramanian*, Andreas Wiese

*Corresponding author for this work

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

Abstract

We study rectangle stabbing problems in which we are given n axis-aligned rectangles in the plane that we want to stab, i.e., we want to select line segments such that for each given rectangle there is a line segment that intersects two opposite edges of it. In the horizontal rectangle stabbing problem (Stabbing), the goal is to find a set of horizontal line segments of minimum total length such that all rectangles are stabbed. In general rectangle stabbing problem, also known as horizontal-vertical stabbing problem (HV-Stabbing), the goal is to find a set of rectilinear (i.e., either vertical or horizontal) line segments of minimum total length such that all rectangles are stabbed. Both variants are NP-hard. Chan, van Dijk, Fleszar, Spoerhase, and Wolff [5] initiated the study of these problems by providing O(1)-approximation algorithms. Recently, Eisenbrand, Gallato, Svensson, and Venzin [11] have presented a QPTAS and a polynomial-time 8-approximation algorithm for Stabbing but it is open whether the problem admits a PTAS. In this paper, we obtain a PTAS for Stabbing, settling this question. For HV-Stabbing, we obtain a (2 + ε) -approximation. We also obtain PTASes for special cases of HV-Stabbing: (i) when all rectangles are squares, (ii) when each rectangle’s width is at most its height, and (iii) when all rectangles are δ -large, i.e., have at least one edge whose length is at least δ, while all edge lengths are at most 1. Our result also implies improved approximations for other problems such as generalized minimum Manhattan network.

Original languageEnglish
Title of host publicationIPCO 2022: Integer Programming and Combinatorial Optimization
EditorsKaren Aardal, Laura Sanità
PublisherSpringer
Pages361-374
Number of pages14
ISBN (Electronic)9783031069017
ISBN (Print)9783031069000
DOIs
Publication statusPublished - 2022
Event23rd International Conference on Integer Programming and Combinatorial Optimization, IPCO 2022 - Eindhoven, Netherlands
Duration: 27 Jun 202229 Jun 2022

Publication series

NameLecture Notes in Computer Science book series (LNCS,volume 13265)
Volume13265 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Integer Programming and Combinatorial Optimization, IPCO 2022
Country/TerritoryNetherlands
CityEindhoven
Period27/06/2229/06/22

Bibliographical note

Funding Information:
Acknowledgement. Arindam Khan was partly supported by Pratiksha Trust Young Investigator Award, Google India Research Award, and Google ExploreCS Award. Andreas Wiese was partially supported by the FONDECYT Regular grant 1200173.

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

Funding

Acknowledgement. Arindam Khan was partly supported by Pratiksha Trust Young Investigator Award, Google India Research Award, and Google ExploreCS Award. Andreas Wiese was partially supported by the FONDECYT Regular grant 1200173.

Keywords

  • Approximation algorithms
  • Geometric optimization
  • Line stabbing
  • Rectangles

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