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dc.contributor.authorMisra, Pranabendu
dc.contributor.authorPanolan, Fahad
dc.contributor.authorRai, Ashutosh
dc.contributor.authorSaurabh, Saket
dc.contributor.authorSharma, Roohani
dc.date.accessioned2021-07-08T08:33:05Z
dc.date.available2021-07-08T08:33:05Z
dc.date.created2020-09-22T20:09:20Z
dc.date.issued2020
dc.identifier.isbn978-3-95977-159-7
dc.identifier.issn1868-8969
dc.identifier.urihttps://hdl.handle.net/11250/2763877
dc.description.abstractIn this paper we study two classical cut problems, namely Multicut and Multiway Cut on chordal graphs and split graphs. In the Multicut problem, the input is a graph G, a collection of 𝓁 vertex pairs (si, ti), i ∈ [𝓁], and a positive integer k and the goal is to decide if there exists a vertex subset S ⊆ V (G) \ {si, ti : i ∈ [𝓁]} of size at most k such that for every vertex pair (si, ti), si and ti are in two different connected components of G − S. In Unrestricted Multicut, the solution S can possibly pick the vertices in the vertex pairs {(si, ti) : i ∈ [𝓁]}. An important special case of the Multicut problem is the Multiway Cut problem, where instead of vertex pairs, we are given a set T of terminal vertices, and the goal is to separate every pair of distinct vertices in T × T. The fixed parameter tractability (FPT) of these problems was a long-standing open problem and has been resolved fairly recently. Multicut and Multiway Cut now admit algorithms with running times 2O(k3)nO(1) and 2knO(1), respectively. However, the kernelization complexity of both these problemsis not fully resolved: while Multicut cannot admit a polynomial kernel under reasonable complexity assumptions, it is a well known open problem to construct a polynomial kernel for Multiway Cut. Towards designing faster FPT algorithms and polynomial kernels for the above mentioned problems, we study them on chordal and split graphs. In particular we obtain the following results. 1. Multicut on chordal graphs admits a polynomial kernel with O(k3𝓁7) vertices. Multiway Cuton chordal graphs admits a polynomial kernel with O(k13) vertices. 2. Multicut on chordal graphs can be solved in time min{O(2k·(k3 + 𝓁)·(n + m)), 2O(𝓁 log k)·(n +m) + 𝓁(n + m)}. Hence Multicut on chordal graphs parameterized by the number of terminals is in XP. 3. Multicut on split graphs can be solved in time min{O(1.2738k+kn+𝓁(n+m), O(2𝓁·𝓁·(n+m))}. Unrestricted Multicut on split graphs can be solved in time O(4𝓁· 𝓁 · (n + m)).en_US
dc.language.isoengen_US
dc.publisherSchloss Dagstuhl – Leibniz Center for Informaticsen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleQuick separation in chordal and split graphsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright the authorsen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doi10.4230/LIPIcs.MFCS.2020.70
dc.identifier.cristin1832296
dc.source.journalLeibniz International Proceedings in Informaticsen_US
dc.source.pagenumber70:1-70:14en_US
dc.identifier.citationLeibniz International Proceedings in Informatics. 2020, 170, 70.en_US
dc.source.volume170en_US
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