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Clustering to given connectivities. (English) Zbl 07650226

Jansen, Bart M. P. (ed.) et al., 14th international symposium on parameterized and exact computation, IPEC 2019, Munich, Germany, September 11–13, 2019. Wadern: Schloss Dagstuhl – Leibniz Zentrum für Informatik. LIPIcs – Leibniz Int. Proc. Inform. 148, Article 18, 17 p. (2019).
Summary: We define a general variant of the graph clustering problem where the criterion of density for the clusters is (high) connectivity. In Clustering to Given Connectivities, we are given an \(n\)-vertex graph \(G\), an integer \(k\), and a sequence \(\Lambda=\langle\lambda_1,\dots,\lambda_t\rangle\) of positive integers and we ask whether it is possible to remove at most \(k\) edges from \(G\) such that the resulting connected components are exactly \(t\) and their corresponding edge connectivities are lower-bounded by the numbers in \(\Lambda\). We prove that this problem, parameterized by \(k\), is fixed parameter tractable, i.e., can be solved by an \(f(k)\cdot n^{O(1)}\)-step algorithm, for some function \(f\) that depends only on the parameter \(k\). Our algorithm uses the recursive understanding technique that is especially adapted so to deal with the fact that we do not impose any restriction to the connectivity demands in \(\Lambda\).
For the entire collection see [Zbl 1433.68020].

MSC:

68Q25 Analysis of algorithms and problem complexity
68Q27 Parameterized complexity, tractability and kernelization
68Wxx Algorithms in computer science