GAJARSKÝ, Jakub, Petr HLINĚNÝ, Martin KOUTECKÝ and Shmuel ONN. Parameterized Shifted Combinatorial Optimization. In Y. Cao and J. Chen. International Computing and Combinatorics Conference COCOON 2017 (LNCS, volume 10392). Hong Kong: Springer International Publishing AG, 2017, p. 224-236. ISBN 978-3-319-62388-7. Available from: https://dx.doi.org/10.1007/978-3-319-62389-4_19.
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Basic information
Original name Parameterized Shifted Combinatorial Optimization
Authors GAJARSKÝ, Jakub (703 Slovakia, belonging to the institution), Petr HLINĚNÝ (203 Czech Republic, guarantor, belonging to the institution), Martin KOUTECKÝ (203 Czech Republic) and Shmuel ONN (376 Israel).
Edition Hong Kong, International Computing and Combinatorics Conference COCOON 2017 (LNCS, volume 10392), p. 224-236, 13 pp. 2017.
Publisher Springer International Publishing AG
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14330/17:00095083
Organization unit Faculty of Informatics
ISBN 978-3-319-62388-7
Doi http://dx.doi.org/10.1007/978-3-319-62389-4_19
UT WoS 000771461800019
Keywords in English Combinatorial optimization; Shifted problem; Treewidth; MSO logic; MSO partitioning
Tags core_A, firank_A, formela-conference
Tags International impact, Reviewed
Changed by Changed by: Mgr. Michal Petr, učo 65024. Changed: 16/5/2022 15:47.
Abstract
Shifted combinatorial optimization is a new nonlinear optimization framework which is a broad extension of standard combinatorial optimization, involving the choice of several feasible solutions at a time. This framework captures well studied and diverse problems ranging from so-called vulnerability problems to sharing and partitioning problems. In particular, every standard combinatorial optimization problem has its shifted counterpart, which is typically much harder. Already with explicitly given input set the shifted problem may be NP-hard. In this article we initiate a study of the parameterized complexity of this framework. First we show that shifting over an explicitly given set with its cardinality as the parameter may be in XP, FPT or P, depending on the objective function. Second, we study the shifted problem over sets definable in MSO logic (which includes, e.g., the well known MSO partitioning problems). Our main results here are that shifted combinatorial optimization over MSO definable sets is in XP with respect to the MSO formula and the treewidth (or more generally clique-width) of the input graph, and is W[1]-hard even under further severe restrictions.
Links
GBP202/12/G061, research and development projectName: Centrum excelence - Institut teoretické informatiky (CE-ITI) (Acronym: CE-ITI)
Investor: Czech Science Foundation
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