Max Coverage—Randomized LP Rounding

Randomized Rounding for Routing and Covering Problems: Experiments and Improvements

Following previous theoretical work by Srinivasan (FOCS 2001) and the first author (STACS 2006) and a first experimental evaluation on random instances (ALENEX 2009), we investigate how the recently developed different approaches to generate randomized roundings satisfying disjoint cardinality constraints behave when used in two classical algorithmic problems, namely low-congestion routing in n...

Simpler 3/4-Approximation Algorithms for MAX SAT

We consider the recent randomized 3 4 -algorithm for MAX SAT of Poloczek and Schnitger. We give a much simpler set of probabilities for setting the variables to true or false, which achieve the same expected performance guarantee. Our algorithm suggests a conceptually simple way to get a deterministic algorithm: rather than comparing to an unknown optimal solution, we instead compare the algori...

Randomized Approximation of MAX-CUT

1 Last Class In the previous class we discussed averaging arguments, derandomization, the method of conditional expectation, and looked at the general technique of relaxation and randomized rounding with respect to MAX-SAT. To solve (approximate) MAX-SAT, we relaxed the requirement that the variables be boolean and instead let them take on real values in the interval 0; 1]. We then solved the r...

Approximation Algorithms: LP Relaxation, Rounding, and Randomized Rounding Techniques

Hybrid approximation for minimum-cost target coverage in wireless sensor networks

This paper presents a hybrid approximation scheme for the Max-SNPcomplete minimum-cost target coverage problem in wireless sensor networks. LP-rounding and set-cover selection are polynomial-time approximations for this problem. Our hybrid scheme combines these two methods using a crafted convex combination. We show that the hybrid scheme with appropriately chosen coefficients produces much bet...