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Lift-and-Project Methods for Set Cover and Knapsack

机译:布景和背包的提起和投影方法

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We study the applicability of lift-and-project methods to the Set Cover and Knapsack problems. Inspired by recent work of Kar-lin, Mathieu, and Nguyen [IPCO 2011], who examined this connection for Knapsack, we consider the applicability and limitations of these methods for Set Cover, as well as extending extending the existing results for Knapsack. For the Set Cover problem, Cygan, Kowalik, and Wykurz [IPL 2009] gave sub-exponential-time approximation algorithms with approximation ratios better than Inn. We present a very simple combinatorial algorithm which has nearly the same time-approximation tradeoff as the algorithm of Cygan et al. We then adapt this to an LP-based algorithm using the LP hierarchy of Lovasz and Schrijver. However, our approach involves the trick of "lifting the objective function". We show that this trick is essential, by demonstrating an integrality gap of (1 - ε) In n at level Ω(n) of the stronger LP hierarchy of Sherali and Adams (when the objective function is not lifted). Finally, we show that the SDP hierarchy of Lovasz and Schrijver (LS_+) reduces the integrality gap for Knapsack to (1 + ε) at level O(1). This stands in contrast to Set Cover (where the work of Aleknovich, Arora, and Tourlakis [STOC 2005] rules out any improvement using LS_+), and extends the work of Karlin et al., who demonstrated such an improvement only for the more powerful SDP hierarchy of Lasserre. Our LS_+ based rounding and analysis are quite different from theirs (in particular, not relying on the decomposition theorem they prove for the Lasserre hierarchy), and to the best of our knowledge represents the first explicit demonstration of such a reduction in the integrality gap of LS_+ relaxations after a constant number of rounds.
机译:我们研究了提升和投影方法对布景和背包问题的适用性。受到Kar-lin,Mathieu和Nguyen [IPCO 2011]近期工作的启发,他们研究了背包的这种连接方式,我们考虑了这些方法在Set Cover中的适用性和局限性,以及扩展了背包的现有结果。对于Set Cover问题,Cygan,Kowalik和Wykurz [IPL 2009]给出了次指数时间近似算法,其近似比率比Inn更好。我们提出了一种非常简单的组合算法,该算法具有与Cygan等人的算法几乎相同的时间近似折衷。然后,我们使用Lovasz和Schrijver的LP层次结构将其调整为基于LP的算法。但是,我们的方法涉及“提升目标函数”的技巧。我们通过在Sherali和Adams的较强LP层次的Ω(n)上证明(1-ε)In n的积分缺口(当不解除目标函数时)显示出这一技巧是必不可少的。最后,我们证明了Lovasz和Schrijver(LS_ +)的SDP层次在O(1)级将背包背负的完整性差距减小到(1 +ε)。这与Set Cover(Aleknovich,Arora和Tourlakis [STOC 2005]的工作排除了使用LS_ +进行的任何改进)形成鲜明对比,并扩展了Karlin等人的工作,他们仅在更多方面证明了这种改进。 Lasserre强大的SDP层次结构。我们基于LS_ +的舍入和分析与它们的舍入和分析有很大不同(特别是,不依赖于他们为Lasserre层次结构证明的分解定理),并且据我们所知,这是首次证明了这种完整性差距的减小。恒定轮数后LS_ +的松弛。

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