Time-approximation trade-offs for inapproximable problems
Bonnet, Édouard; Lampis, Michael; Paschos, Vangelis (2018), Time-approximation trade-offs for inapproximable problems, Journal of Computer and System Sciences, 92, p. 171-180. 10.1016/j.jcss.2017.09.009
Type
Article accepté pour publication ou publiéExternal document link
https://arxiv.org/abs/1502.05828v1Date
2018Journal name
Journal of Computer and System SciencesVolume
92Publisher
Elsevier
Pages
171-180
Publication identifier
Metadata
Show full item recordAuthor(s)
Bonnet, Édouard
Lampis, Michael

Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Paschos, Vangelis
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
In this paper we focus on problems inapproximable in polynomial time and explore how quickly their approximability improves as the allowed running time is gradually increased from polynomial to (sub-)exponential. We tackle a number of problems: For Min Independent Dominating Set, Max Induced Path, Forest and Tree, for any , a simple, known scheme gives an approximation ratio of r in time roughly . We show that, if this running time could be significantly improved, the ETH would fail. For Max Minimal Vertex Cover we give a -approximation in time . We match this with a similarly tight result. We also give a -approximation for Min ATSP in time and an r-approximation for Max Grundy Coloring in time . Finally, we investigate the approximability of Min Set Cover, when measuring the running time as a function of the number of sets in the input.Subjects / Keywords
Approximation algorithms; Exponential algorithms; Sub-exponential algorithms; Hardness of approximationRelated items
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