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.ESA.2020.58
URN: urn:nbn:de:0030-drops-129243
URL: https://drops.dagstuhl.de/opus/volltexte/2020/12924/
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Henzinger, Monika ; Khan, Shahbaz ; Paul, Richard ; Schulz, Christian

Dynamic Matching Algorithms in Practice

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LIPIcs-ESA-2020-58.pdf (1 MB)


Abstract

In recent years, significant advances have been made in the design and analysis of fully dynamic maximal matching algorithms. However, these theoretical results have received very little attention from the practical perspective. Few of the algorithms are implemented and tested on real datasets, and their practical potential is far from understood. In this paper, we attempt to bridge the gap between theory and practice that is currently observed for the fully dynamic maximal matching problem. We engineer several algorithms and empirically study those algorithms on an extensive set of dynamic instances.

BibTeX - Entry

@InProceedings{henzinger_et_al:LIPIcs:2020:12924,
  author =	{Monika Henzinger and Shahbaz Khan and Richard Paul and Christian Schulz},
  title =	{{Dynamic Matching Algorithms in Practice}},
  booktitle =	{28th Annual European Symposium on Algorithms (ESA 2020)},
  pages =	{58:1--58:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-162-7},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{173},
  editor =	{Fabrizio Grandoni and Grzegorz Herman and Peter Sanders},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12924},
  URN =		{urn:nbn:de:0030-drops-129243},
  doi =		{10.4230/LIPIcs.ESA.2020.58},
  annote =	{Keywords: Matching, Dynamic Matching, Blossom Algorithm}
}

Keywords: Matching, Dynamic Matching, Blossom Algorithm
Collection: 28th Annual European Symposium on Algorithms (ESA 2020)
Issue Date: 2020
Date of publication: 26.08.2020
Supplementary Material: Source code and instances are available at https://github.com/schulzchristian/DynMatch.


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