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This paper deals with robust optimization applied to network flows. Tworobust variants of the minimum-cost integer flow problem are considered.Thereby, uncertainty in problem formulation is limited to arc unit costs andexpressed by a finite set of explicitly given scenarios. It is shown that bothproblem variants are NP-hard. To solve the considered variants, severalheuristics based on local search or evolutionary computing are proposed. Theheuristics are experimentally evaluated on appropriate problem instances.

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