License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ISAAC.2017.1
URN: urn:nbn:de:0030-drops-82738
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2017/8273/
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Iwata, Satoru

Weighted Linear Matroid Parity

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LIPIcs-ISAAC-2017-1.pdf (0.4 MB)

Abstract

The matroid parity (or matroid matching) problem, introduced as a common generalization of matching and matroid intersection problems, is so general that it requires an exponential number of oracle calls. Nevertheless, Lovasz (1978) showed that this problem admits a min-max formula and a polynomial algorithm for linearly represented matroids. Since then efficient algorithms have been developed for the linear matroid parity problem.

This talk presents a recently developed polynomial-time algorithm for the weighted linear matroid parity problem. The algorithm builds on a polynomial matrix formulation using Pfaffian and adopts a primal-dual approach based on the augmenting path algorithm of Gabow and Stallmann (1986) for the unweighted problem.

BibTeX - Entry

@InProceedings{iwata:LIPIcs:2017:8273,
  author =	{Satoru Iwata},
  title =	{{Weighted Linear Matroid Parity}},
  booktitle =	{28th International Symposium on Algorithms and Computation (ISAAC 2017)},
  pages =	{1:1--1:5},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-054-5},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{92},
  editor =	{Yoshio Okamoto and Takeshi Tokuyama},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2017/8273},
  URN =		{urn:nbn:de:0030-drops-82738},
  doi =		{10.4230/LIPIcs.ISAAC.2017.1},
  annote =	{Keywords: Matroid, matching, Pfaffian, polynomial-time algorithm}
}

Keywords: Matroid, matching, Pfaffian, polynomial-time algorithm
Collection: 28th International Symposium on Algorithms and Computation (ISAAC 2017)
Issue Date: 2017
Date of publication: 07.12.2017

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