Understanding Set Cover: Sub-exponential Time Approximations and Lift-and-Project Methods
Eden Chlamtac, Zac Friggstad, Konstantinos Georgiou

TL;DR
This paper explores the use of lift-and-project methods to improve approximation algorithms for Set Cover, demonstrating that certain hierarchies of LP and SDP relaxations can match combinatorial algorithms' performance and analyzing their integrality gaps.
Contribution
The paper introduces a lift-and-project approach for Set Cover that matches existing combinatorial algorithms' performance and analyzes the limitations of LP and SDP hierarchies in reducing integrality gaps.
Findings
Lift-and-project methods match combinatorial algorithms' time-approximation tradeoff.
LP hierarchy of Lovasz and Schrijver can match combinatorial performance with objective lifting.
Stronger LP hierarchy of Sherali and Adams does not significantly reduce integrality gap without objective lifting.
Abstract
Recently, Cygan, Kowalik, and Wykurz [IPL 2009] gave sub-exponential-time approximation algorithms for the Set-Cover problem with approximation ratios better than ln(n). In light of this result, it is natural to ask whether such improvements can be achieved using lift-and-project methods. We present a simpler combinatorial algorithm which has nearly the same time-approximation tradeoff as the algorithm of Cygan et al., and which lends itself naturally to a lift-and-project based approach. At a high level, our approach is similar to the recent work of Karlin, Mathieu, and Nguyen [IPCO 2011], who examined a known PTAS for Knapsack (similar to our combinatorial Set-Cover algorithm) and its connection to hierarchies of LP and SDP relaxations for Knapsack. For Set-Cover, we show that, indeed, using the trick of "lifting the objective function", we can match the performance of our…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Optimization and Search Problems
