从Gap-ETH到fpt -不可逼近性:派系、支配集等

Parinya Chalermsook, Marek Cygan, G. Kortsarz, Bundit Laekhanukit, Pasin Manurangsi, Danupon Nanongkai, L. Trevisan
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引用次数: 86

摘要

我们考虑从近似算法,次指数时间算法和固定参数可处理算法之间的交叉领域产生的问题。已经被问过几次的问题(例如,[Marx, 2008;Fellow等人,2012;唐尼和Fellow 2013])是否存在一个非平凡的fpt逼近算法来解决由最优解的大小参数化的最大团(Clique)和最小支配集(DomSet)问题。特别是,让opt为最优,N为输入的大小,是否有一种算法可以运行int(opt) poly(N) time并输出大小为f(opt)的解,对于任何独立于N的函数t和f(对于Clique,我们希望f(opt)=Ω(1))?在本文中,我们证明了对于任何函数f(例如,即使f是指数函数或Ackermann函数),Clique和DomSet都不允许非平凡的fpt逼近算法,即对于Clique不存在o(opt)- fpt逼近算法,对于DomSet也不存在f(opt)- fpt逼近算法。事实上,我们的结果暗示了更强大的东西:解决Clique和DomSet的最好方法,即使是近似的,本质上是枚举所有的可能性。我们的结果在Gap指数时间假设(Gap- eth)下成立[Dinur, 2016, Manurangsi & Raghavendra 2016],这表明没有2^{o(n)}时间算法可以区分可满足的3SAT公式和对于某些常数c ≈甚至(1 - c)-可满足的3SAT公式;0.除了Clique和DomSet,我们还排除了最大平衡Biclique的非平凡fpt逼近问题,寻找具有遗传性质的最大子图(例如,最大诱导平面子图)的问题,以及二部图的最大诱导匹配问题。以前,已知这些问题的精确版本是W[1]-hard [Lin, 2015;Khot & Raman, 2000;Moser & Sikdar, 2009]。此外,我们排除了k^{o(1)}- fpt近似算法对于den最k- subgraph,尽管这个比率还不匹配平凡的o(k)-近似算法。据我们所知,先前的结果只排除了Clique的常数因子近似[Hajiaghayi et al., 2013;KK13, Bonnet等,2015]和log^{1/4+c}(opt)逼近DomSet对于任意常数c ≈[陈林,2016]。我们在Clique上的结果显著改善了[Hajiaghayi et al., 2013;Bonnet et al., 2015]。然而,我们在DomSet上的结果与[Chen & Lin, 2016]无法比较,因为他们的结果在ETH下成立,而我们的结果在Gap-ETH下成立,这是一个更强的假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From Gap-ETH to FPT-Inapproximability: Clique, Dominating Set, and More
We consider questions that arise from the intersection between theareas of approximation algorithms, subexponential-time algorithms, and fixed-parameter tractable algorithms. The questions, which have been asked several times (e.g., [Marx, 2008; Fellow et al., 2012; Downey & Fellow 2013]) are whether there is a non-trivial FPT-approximation algorithm for the Maximum Clique (Clique) and Minimum Dominating Set (DomSet) problems parameterized by the size of the optimal solution. In particular, letting opt be the optimum and N be the size of the input, is there an algorithm that runs int(opt) poly(N) time and outputs a solution of size f(opt), forany functions t and f that are independent of N (for Clique, we want f(opt)=Ω(1))? In this paper, we show that both Clique and DomSet admit no non-trivial FPT-approximation algorithm, i.e., there is no o(opt)-FPT-approximation algorithm for Clique and no f(opt)-FPT-approximation algorithm for DomSet, for any function f (e.g., this holds even if f is an exponential or the Ackermann function). In fact, our results imply something even stronger: The best way to solve Clique and DomSet, even approximately, is to essentially enumerate all possibilities. Our results hold under the Gap Exponential Time Hypothesis (Gap-ETH) [Dinur, 2016, Manurangsi & Raghavendra 2016], which states that no 2^{o(n)}-time algorithm can distinguish between a satisfiable 3SAT formula and one which is not even (1 - c)-satisfiable for some constant c ≈ 0.Besides Clique and DomSet, we also rule out non-trivial FPT-approximation for Maximum Balanced Biclique, the problem of finding maximum subgraphs with hereditary properties (e.g., Maximum Induced Planar Subgraph), and Maximum Induced Matching in bipartite graphs. Previously only exact versions of these problems were known to be W[1]-hard [Lin, 2015; Khot & Raman, 2000; Moser & Sikdar, 2009]. Additionally, we rule out k^{o(1)}-FPT-approximation algorithm for Densest k-Subgraph although this ratio does not yet match the trivial O(k)-approximation algorithm.To the best of our knowledge, prior results only rule out constantfactor approximation for Clique [Hajiaghayi et al., 2013; KK13, Bonnet et al., 2015] and log^{1/4+c}(opt) approximation for DomSet for any constant c ≈ 0 [Chen & Lin, 2016]. Our result on Clique significantly improves on [Hajiaghayi et al., 2013; Bonnet et al., 2015]. However, our result on DomSet is incomparable to [Chen & Lin, 2016] since their results hold under ETH while our results hold under Gap-ETH, which is a stronger assumption.
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