122 research outputs found

    Cluster Editing: Kernelization based on Edge Cuts

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    Kernelization algorithms for the {\sc cluster editing} problem have been a popular topic in the recent research in parameterized computation. Thus far most kernelization algorithms for this problem are based on the concept of {\it critical cliques}. In this paper, we present new observations and new techniques for the study of kernelization algorithms for the {\sc cluster editing} problem. Our techniques are based on the study of the relationship between {\sc cluster editing} and graph edge-cuts. As an application, we present an O(n2){\cal O}(n^2)-time algorithm that constructs a 2k2k kernel for the {\it weighted} version of the {\sc cluster editing} problem. Our result meets the best kernel size for the unweighted version for the {\sc cluster editing} problem, and significantly improves the previous best kernel of quadratic size for the weighted version of the problem

    PACE Solver Description: Cluster Editing Kernelization Using CluES

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    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)

    The PACE 2021 Parameterized Algorithms and Computational Experiments Challenge: Cluster Editing

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    The Parameterized Algorithms and Computational Experiments challenge (PACE) 2021 was devoted to engineer algorithms solving the NP-hard Cluster Editing problem, also known as Correlation Clustering: Given an undirected graph the task is to compute a minimum number of edges to insert or remove in a way that the resulting graph is a cluster graph, that is, a graph in which each connected component is a clique. Altogether 67 participants from 21 teams, 11 countries, and 3 continents submitted their implementations to the competition. In this report, we describe the setup of the challenge, the selection of benchmark instances, and the ranking of the participating teams. We also briefly discuss the approaches used in the submitted solvers
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