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.
@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/entities/document/10.4230/LIPIcs.IPEC.2021.31}, URN = {urn:nbn:de:0030-drops-154147}, doi = {10.4230/LIPIcs.IPEC.2021.31}, annote = {Keywords: cluster editing, local search, variable neighborhood search} }
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