2-Approximating Feedback Vertex Set in Tournaments
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作者:
Lokshtanov, Daniel
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Univ Calif Santa Barbara, Santa Barbara, CA 93106 USAUniv Calif Santa Barbara, Santa Barbara, CA 93106 USA
Lokshtanov, Daniel
[1
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Misra, Pranabendu
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Max Planck Inst Informat, Saarbrucken, GermanyUniv Calif Santa Barbara, Santa Barbara, CA 93106 USA
Misra, Pranabendu
[2
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Mukherjee, Joydeep
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Indian Stat Inst, Kolkata, India
Ramakrishna Mission Vivekananda Educ & Res Inst, Kolkata, IndiaUniv Calif Santa Barbara, Santa Barbara, CA 93106 USA
Mukherjee, Joydeep
[3
,4
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Panolan, Fahad
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Indian Inst Technol, Hyderabad, IndiaUniv Calif Santa Barbara, Santa Barbara, CA 93106 USA
Panolan, Fahad
[5
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Philip, Geevarghese
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Chennai Math Inst, Chennai, Tamil Nadu, India
IRL 2000 ReLaX, Chennai, Tamil Nadu, IndiaUniv Calif Santa Barbara, Santa Barbara, CA 93106 USA
Philip, Geevarghese
[6
,7
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Saurabh, Saket
[7
,8
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机构:
[1] Univ Calif Santa Barbara, Santa Barbara, CA 93106 USA
[2] Max Planck Inst Informat, Saarbrucken, Germany
[3] Indian Stat Inst, Kolkata, India
[4] Ramakrishna Mission Vivekananda Educ & Res Inst, Kolkata, India
[5] Indian Inst Technol, Hyderabad, India
[6] Chennai Math Inst, Chennai, Tamil Nadu, India
[7] IRL 2000 ReLaX, Chennai, Tamil Nadu, India
[8] HBNI, Inst Math Sci, Chennai, Tamil Nadu, India
A tournament is a directed graph T such that every pair of vertices is connected by an arc. A feedback vertex set is a set S of vertices in T such that T - S is acyclic. We consider the FEEDBACK VERTEX SET problem in tournaments. Here the input is a tournament T and a weight function w : V(T) -> N and the task is to find a feedback vertex set S in T minimizing w(S) = Sigma(v is an element of S) w(v). Rounding optimal solutions to the natural LP-relaxation of this problem yields a simple 3-approximation algorithm. This has been improved to 2.5 by Cai et al. [SICOMP 2000], and subsequently to 7/3 by Mnich et al. [ESA 2016]. In this paper we give the first polynomial time factor 2 approximation algorithm for this problem. Assuming the Unique Games conjecture, this is the best possible approximation ratio achievable in polynomial time.