Heuristic solutions to robust variants of the minimum-cost integer flow problem

This paper deals with robust optimization applied to network flows. We consider two robust variants of the minimum-cost integer flow problem. Thereby, uncertainty in problem formulation is limited to arc costs and expressed by a finite set of explicitly given scenarios. It turns out that both problem variants are NP-hard. To solve the considered variants, we propose several heuristics based on local search or evolutionary computing. We also evaluate our heuristics experimentally on appropriate problem instances.