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Parameterized algorithms for min-max multiway cut and list digraph homomorphism

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Date
2017
Link to item file
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01487567
Dewey
Principes généraux des mathématiques
Sujet
Parameterized complexity; Fixed-Parameter Tractable algorithm; Multiway Cut; Digraph homomorphism
Journal issue
Journal of Computer and System Sciences
Volume
86
Publication date
2017
Article pages
191-206
Publisher
Elsevier
DOI
http://dx.doi.org/10.1016/j.jcss.2017.01.003
URI
https://basepub.dauphine.fr/handle/123456789/20785
Collections
  • LAMSADE : Publications
Metadata
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Author
Kim, Eun Jung
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Paul, Christophe
Sau Valls, Ignasi
Thilikos, Dimitrios M.
Type
Article accepté pour publication ou publié
Abstract (EN)
In this paper we design FPT-algorithms for two parameterized problems. The first is List Digraph Homomorphism: given two digraphs G and H and a list of allowed vertices of H for every vertex of G, the question is whether there exists a homomorphism from G to H respecting the list constraints. The second problem is a variant of Multiway Cut, namely Min-Max Multiway Cut: given a graph G, a non-negative integer `, and a set T of r terminals, the question is whether we can partition the vertices of G into r parts such that (a) each part contains one terminal and (b) there are at most ` edges with only one endpoint in this part. Weparameterize List Digraph Homomorphism by the number w of edges of G that are mapped to non-loop edges of H and we give a time 2O(`·log h+`2·log `)· n4 log n algorithm, where h is the order of the host graph H. We also prove that Min-Max Multiway Cut can be solved in time 2O((`r)2log `r)· n4· log n. Our approach introduces a general problem, called List Allocation, whose expressive power permits the design of parameterized reductions of both aforementioned problems to it. Then our results are based on an FPT-algorithm for the List Allocation problem that is designed using a suitable adaptation of the randomized contractions technique.

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