Parameterized shifted combinatorial optimization

J 2019

Parameterized shifted combinatorial optimization

GAJARSKÝ, Jakub, Petr HLINĚNÝ, Martin KOUTECKÝ and Shmuel ONN

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

Journal of Computer and System Sciences, SAN DIEGO, Academic Press, 2019, 0022-0000

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

DOI open access preprint

Impact factor

Impact factor: 1.494

RIV identification code

RIV/00216224:14330/19:00108272

Organization unit

Faculty of Informatics

DOI

http://dx.doi.org/10.1016/j.jcss.2018.06.002

UT WoS

000448636500003

Keywords in English

Combinatorial optimization; Shifted problem; Treewidth; MSO logic; MSO partitioning

Abstract

V originále

Shifted combinatorial optimization is a new nonlinear optimization framework broadly extending standard combinatorial optimization, involving the choice of several feasible solutions simultaneously. This framework captures well studied and diverse problems, from sharing and partitioning to so-called vulnerability problems. In particular, every standard combinatorial optimization problem has its shifted counterpart, typically harder. Already with explicitly given input set SCO may be NP-hard. Here we initiate a study of the parameterized complexity of this framework. First we show that SCO over an explicitly given set parameterized by its cardinality may be in XP, FPT or P, depending on the objective function. Second, we study SCO over sets definable in MSO logic (which includes, e.g., the well known MSO-partitioning problems). Our main results are that SCO over MSO definable sets is in XP parameterized by the MSO formula and treewidth (or clique-width) of the input graph, and W[1]-hard even under further severe restrictions.

Links

GBP202/12/G061, research and development project

Name: Centrum excelence - Institut teoretické informatiky (CE-ITI) (Acronym: CE-ITI)

Investor: Czech Science Foundation

Citovat

GAJARSKÝ, Jakub, Petr HLINĚNÝ, Martin KOUTECKÝ and Shmuel ONN. Parameterized shifted combinatorial optimization. Journal of Computer and System Sciences. SAN DIEGO: Academic Press, 2019, vol. 99, No 1, p. 53-71. ISSN 0022-0000. Available from: https://dx.doi.org/10.1016/j.jcss.2018.06.002.

@article{1646042,
   author = {Gajarský, Jakub and Hliněný, Petr and Koutecký, Martin and Onn, Shmuel},
   article_location = {SAN DIEGO},
   article_number = {1},
   doi = {http://dx.doi.org/10.1016/j.jcss.2018.06.002},
   keywords = {Combinatorial optimization; Shifted problem; Treewidth; MSO logic; MSO partitioning},
   language = {eng},
   issn = {0022-0000},
   journal = {Journal of Computer and System Sciences},
   title = {Parameterized shifted combinatorial optimization},
   url = {http://dx.doi.org/10.1016/j.jcss.2018.06.002},
   volume = {99},
   year = {2019}
}

TY  - JOUR
ID  - 1646042
AU  - Gajarský, Jakub - Hliněný, Petr - Koutecký, Martin - Onn, Shmuel
PY  - 2019
TI  - Parameterized shifted combinatorial optimization
JF  - Journal of Computer and System Sciences
VL  - 99
IS  - 1
SP  - 53-71
EP  - 53-71
PB  - Academic Press
SN  - 00220000
KW  - Combinatorial optimization
KW  - Shifted problem
KW  - Treewidth
KW  - MSO logic
KW  - MSO partitioning
UR  - http://dx.doi.org/10.1016/j.jcss.2018.06.002
N2  - Shifted combinatorial optimization is a new nonlinear optimization framework broadly extending standard combinatorial optimization, involving the choice of several feasible solutions simultaneously. This framework captures well studied and diverse problems, from sharing and partitioning to so-called vulnerability problems. In particular, every standard combinatorial optimization problem has its shifted counterpart, typically harder. Already with explicitly given input set SCO may be NP-hard. Here we initiate a study of the parameterized complexity of this framework. First we show that SCO over an explicitly given set parameterized by its cardinality may be in XP, FPT or P, depending on the objective function. Second, we study SCO over sets definable in MSO logic (which includes, e.g., the well known MSO-partitioning problems). Our main results are that SCO over MSO definable sets is in XP parameterized by the MSO formula and treewidth (or clique-width) of the input graph, and W[1]-hard even under further severe restrictions.
ER  -

GAJARSKÝ, Jakub, Petr HLINĚNÝ, Martin KOUTECKÝ and Shmuel ONN. Parameterized shifted combinatorial optimization. \textit{Journal of Computer and System Sciences}. SAN DIEGO: Academic Press, 2019, vol.~99, No~1, p.~53-71. ISSN~0022-0000. Available from: https://dx.doi.org/10.1016/j.jcss.2018.06.002.

Detailed Information on Publication Record