Approximating Combinatorial Optimization Problems with Uncertain Costs and the OWA Criterion

In this paper a class combinatorial optimization problems with uncertain costs is discussed. This uncertainty is modeled by specifying a scenario set containing K distinct cost vectors. In order to choose a solution the Ordered Weighted Averaging aggregation operator (OWA) is used. For most classical problems, for example network problems, minimizing OWA is NP-hard even for two scenarios. In this paper some positive and negative approximation results for the problem are shown.