
Approximation Algorithms and LP Relaxations for Scheduling Problems Related to MinSum Set Cover
We consider singlemachine scheduling problems that are natural generali...
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Toward a Dichotomy for Approximation of Hcoloring
The minimum cost homomorphism problem (MinHOM) is a natural optimization...
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On the Complexity of BWTruns Minimization via Alphabet Reordering
We present the first set of results on the computational complexity of m...
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Approximating Biobjective Minimization Problems Using General Ordering Cones
This article investigates the approximation quality achievable for biobj...
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On the Approximability of Multistage MinSum Set Cover
We investigate the polynomialtime approximability of the multistage ver...
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Fair and Reliable Reconnections for Temporary Disruptions in Electric Distribution Networks using Submodularity
We analyze a distributed approach for automatically reconfiguring distri...
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A WaterFilling PrimalDual Algorithm for Approximating NonLinear Covering Problems
Obtaining strong linear relaxations of capacitated covering problems con...
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A General Framework for Approximating Min Sum Ordering Problems
We consider a large family of problems in which an ordering of a finite set must be chosen to minimize some weighted sum of costs. This family includes variations of Min Sum Set Cover, several scheduling and search problems, and problems in Boolean function evaluation. We define a new problem, called the Min Sum Ordering Problem (MSOP) which generalizes all these problems using a cost and a weight function on subsets of a finite set. Assuming a polynomial time αapproximation algorithm for the problem of finding a subset whose ratio of weight to cost is maximal, we show that under very minimal assumptions, there is a polynomial time 4 αapproximation algorithm for MSOP. This approximation result generalizes a proof technique used for several distinct problems in the literature. We apply our approximation result to obtain a number of new approximation results.
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