4 research outputs found
Lagrangian Relaxation and Partial Cover (Extended Abstract)
Lagrangian relaxation has been used extensively in the design of
approximation algorithms. This paper studies its strengths and
limitations when applied to Partial Cover.
We show that for Partial Cover in general no algorithm that uses
Lagrangian relaxation and a Lagrangian Multiplier Preserving (LMP)
-approximation as a black box can yield an approximation
factor better than~. This matches the upper bound
given by K"onemann et al. (ESA 2006, pages
468--479).
Faced with this limitation we study a specific, yet broad class of
covering problems: Partial Totally Balanced Cover. By carefully
analyzing the inner workings of the LMP algorithm we are able to
give an almost tight characterization of the integrality gap of the
standard linear relaxation of the problem. As a consequence we
obtain improved approximations for the Partial version of Multicut
and Path Hitting on Trees, Rectangle Stabbing, and Set Cover with
-Blocks
Scheduling with Outliers
In classical scheduling problems, we are given jobs and machines, and have to
schedule all the jobs to minimize some objective function. What if each job has
a specified profit, and we are no longer required to process all jobs -- we can
schedule any subset of jobs whose total profit is at least a (hard) target
profit requirement, while still approximately minimizing the objective
function?
We refer to this class of problems as scheduling with outliers. This model
was initiated by Charikar and Khuller (SODA'06) on the minimum max-response
time in broadcast scheduling. We consider three other well-studied scheduling
objectives: the generalized assignment problem, average weighted completion
time, and average flow time, and provide LP-based approximation algorithms for
them. For the minimum average flow time problem on identical machines, we give
a logarithmic approximation algorithm for the case of unit profits based on
rounding an LP relaxation; we also show a matching integrality gap. For the
average weighted completion time problem on unrelated machines, we give a
constant factor approximation. The algorithm is based on randomized rounding of
the time-indexed LP relaxation strengthened by the knapsack-cover inequalities.
For the generalized assignment problem with outliers, we give a simple
reduction to GAP without outliers to obtain an algorithm whose makespan is
within 3 times the optimum makespan, and whose cost is at most (1 + \epsilon)
times the optimal cost.Comment: 23 pages, 3 figure
Proceedings of the 26th International Symposium on Theoretical Aspects of Computer Science (STACS'09)
The Symposium on Theoretical Aspects of Computer Science (STACS) is held alternately in France and in Germany. The conference of February 26-28, 2009, held in Freiburg, is the 26th in this series. Previous meetings took place in Paris (1984), Saarbr¨ucken (1985), Orsay (1986), Passau (1987), Bordeaux (1988), Paderborn (1989), Rouen (1990), Hamburg (1991), Cachan (1992), W¨urzburg (1993), Caen (1994), M¨unchen (1995), Grenoble (1996), L¨ubeck (1997), Paris (1998), Trier (1999), Lille (2000), Dresden (2001), Antibes (2002), Berlin (2003), Montpellier (2004), Stuttgart (2005), Marseille (2006), Aachen (2007), and Bordeaux (2008). ..