Faster computation of path-width

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Tree-width and path-width are widely successful concepts.Many NP-hard problems have efficient solutions when restricted to graphs of bounded tree-width.Many efficient algorithms are based on a tree decomposition.Sometimes the more restricted path decomposition is required.The bottleneck for such algorithms is often the computation of the width and a corresponding tree or path decomposition.For graphs with n vertices and tree-width or path-width k, the standard linear time algorithm to compute these decompositions dates back to 1996.Its running time is linear in n and exponential in k3 and not usable in practice.Here we present a more efficient algorithm to compute the path-width and provide a path decomposition.Its running time is 2O(k2)n.In the classical algorithm of Bodlaender and Kloks, the path decomposition is computed from a tree decomposition.Here, an optimal path decomposition is computed from a path decomposition of about twice the width.The latter is computed from a constant factor smaller graph.

Original languageEnglish (US)
Title of host publicationCombinatorial Algorithms - 27th International Workshop, IWOCA 2016, Proceedings
EditorsVeli Mäkinen, Simon J. Puglisi, Leena Salmela
PublisherSpringer Verlag
Pages385-396
Number of pages12
ISBN (Print)9783319445427
DOIs
StatePublished - 2016
Event27th International Workshop on Combinatorial Algorithms, IWOCA 2016 - Helsinki, Finland
Duration: Aug 17 2016Aug 19 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9843 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other27th International Workshop on Combinatorial Algorithms, IWOCA 2016
Country/TerritoryFinland
CityHelsinki
Period8/17/168/19/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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