PACE Solver Description: Cluster Editing Kernelization Using CluES

Author Sylwester Swat

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Sylwester Swat
  • Institute of Computing Science, Poznań University of Technology, Poland

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Sylwester Swat. PACE Solver Description: Cluster Editing Kernelization Using CluES. In 16th International Symposium on Parameterized and Exact Computation (IPEC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 214, pp. 35:1-35:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


This article briefly describes the most important algorithms and techniques used in the cluster editing kernelization solver called "CluES", submitted to the 6th Parameterized Algorithms and Computational Experiments Challenge (PACE 2021).

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Graph algorithms
  • Cluster editing
  • kernelization
  • graph algorithms
  • PACE 2021


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  1. Sebastian Böcker, Sebastian Briesemeister, and Gunnar Klau. Exact algorithms for cluster editing: Evaluation and experiments. Algorithmica, 60:316-334, January 2008. Google Scholar
  2. Jianer Chen and Jie Meng. A 2k kernel for the cluster editing problem. Journal of Computer and System Sciences, 78(1):211-220, 2012. JCSS Knowledge Representation and Reasoning. Google Scholar
  3. Jiong Guo. A more effective linear kernelization for cluster editing. Theor. Comput. Sci., 410:718-726, March 2009. Google Scholar
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