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Improving relaxations for potential-driven network flow problems via acyclic flow orientations

Please always quote using this URN: urn:nbn:de:0297-zib-69622
  • The class of potential-driven network flow problems provides important models for a range of infrastructure networks. For real-world applications, they need to be combined with integer models for switching certain network elements, giving rise to hard-to-solve MINLPs. We observe that on large-scale real-world meshed networks the usually employed relaxations are rather weak due to cycles in the network. We propose acyclic flow orientations as a combinatorial relaxation of feasible solutions of potential-driven flow problems and show how they can be used to strengthen existing relaxations. First computational results indicate that the strengthend model is much tighter than the original relaxation, thus promising a computational advantage.

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Author:Benjamin HillerORCiD, Kai-Helge Becker
Document Type:ZIB-Report
Tag:MINLPs; acyclic orientations; flow orientations; potential-driven network flows
CCS-Classification:G. Mathematics of Computing
Date of first Publication:2018/07/25
Series (Serial Number):ZIB-Report (18-30)
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