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.
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This work has been fully supported by Croatian Science Foundation under the project IP-2018-01-5591. The authors would like to thank the reviewers for their useful remarks on an earlier version of the paper.
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Špoljarec, M., Manger, R. Heuristic solutions to robust variants of the minimum-cost integer flow problem. J Heuristics (2020). https://doi.org/10.1007/s10732-020-09441-1
- Robust optimization
- Network flow
- Minimum-cost flow
- Local search
- Evolutionary computing