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Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.IPEC.2021.31
URN: urn:nbn:de:0030-drops-154147
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2021/15414/
Bläsius, Thomas ;
Fischbeck, Philipp ;
Gottesbüren, Lars ;
Hamann, Michael ;
Heuer, Tobias ;
Spinner, Jonas ;
Weyand, Christopher ;
Wilhelm, Marcus
PACE Solver Description: KaPoCE: A Heuristic Cluster Editing Algorithm
Abstract
The cluster editing problem is to transform an input graph into a cluster graph by performing a minimum number of edge editing operations. A cluster graph is a graph where each connected component is a clique. An edit operation can be either adding a new edge or removing an existing edge. In this write-up we outline the core techniques used in the heuristic cluster editing algorithm of the Karlsruhe and Potsdam Cluster Editing (KaPoCE) framework, submitted to the heuristic track of the 2021 PACE challenge.
BibTeX - Entry
@InProceedings{blasius_et_al:LIPIcs.IPEC.2021.31,
author = {Bl\"{a}sius, Thomas and Fischbeck, Philipp and Gottesb\"{u}ren, Lars and Hamann, Michael and Heuer, Tobias and Spinner, Jonas and Weyand, Christopher and Wilhelm, Marcus},
title = {{PACE Solver Description: KaPoCE: A Heuristic Cluster Editing Algorithm}},
booktitle = {16th International Symposium on Parameterized and Exact Computation (IPEC 2021)},
pages = {31:1--31:4},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-216-7},
ISSN = {1868-8969},
year = {2021},
volume = {214},
editor = {Golovach, Petr A. and Zehavi, Meirav},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2021/15414},
URN = {urn:nbn:de:0030-drops-154147},
doi = {10.4230/LIPIcs.IPEC.2021.31},
annote = {Keywords: cluster editing, local search, variable neighborhood search}
}
