Approximation algorithms for B1-EPG graphs

Dror Epstein, Martin Charles Golumbic, Gila Morgenstern

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

Abstract

The edge intersection graphs of paths on a grid (or EPG graphs) are graphs whose vertices can be represented as simple paths on a rectangular grid such that two vertices are adjacent if and only if the corresponding paths share at least one edge of the grid. We consider the case of single-bend paths, namely, the class known as B1-EPG graphs. The motivation for studying these graphs comes from the context of circuit layout problems. It is known that recognizing B1-EPG graphs is NP-complete, nevertheless, optimization problems when given a set of paths in the grid are of considerable practical interest. In this paper, we show that the coloring problem and the maximum independent set problem are both NP-complete for B1-EPG graphs, even when the EPG representation is given. We then provide efficient 4-approximation algorithms for both of these problems, assuming the EPG representation is given. We conclude by noting that the maximum clique problem can be optimally solved in polynomial time for B1-EPG graphs, even when the EPG representation is not given.

Original languageEnglish
Title of host publicationAlgorithms and Data Structures - 13th International Symposium, WADS 2013, Proceedings
Pages328-340
Number of pages13
DOIs
StatePublished - 2013
Event13th International Symposium on Algorithms and Data Structures, WADS 2013 - London, ON, Canada
Duration: 12 Aug 201314 Aug 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8037 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Symposium on Algorithms and Data Structures, WADS 2013
Country/TerritoryCanada
CityLondon, ON
Period12/08/1314/08/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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