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DOI: 10.4230/LIPIcs.ESA.2020.58

Dynamic Matching Algorithms in Practice

Authors: Monika Henzinger, Shahbaz Khan, Richard Paul, and Christian Schulz

Published in: LIPIcs, Volume 173, 28th Annual European Symposium on Algorithms (ESA 2020)

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.

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Monika Henzinger, Shahbaz Khan, Richard Paul, and Christian Schulz. Dynamic Matching Algorithms in Practice. In 28th Annual European Symposium on Algorithms (ESA 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 173, pp. 58:1-58:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{henzinger_et_al:LIPIcs.ESA.2020.58,
  author =	{Henzinger, Monika and Khan, Shahbaz and Paul, Richard and Schulz, Christian},
  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 =	{Grandoni, Fabrizio and Herman, Grzegorz and Sanders, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2020.58},
  URN =		{urn:nbn:de:0030-drops-129243},
  doi =		{10.4230/LIPIcs.ESA.2020.58},
  annote =	{Keywords: Matching, Dynamic Matching, Blossom Algorithm}
}

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Dynamic Matching Algorithms in Practice

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