Rapidly computing robust minimum capacity s‐t cuts: a case study in solving a sequence of maximum flow problems

Rapidly computing robust minimum capacity s‐t cuts: a case study in solving a sequence of maximum flow problems

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Article ID: iaor20112602
Volume: 184
Issue: 1
Start Page Number: 3
End Page Number: 26
Publication Date: Apr 2011
Journal: Annals of Operations Research
Authors: ,
Keywords: networks: flow
Abstract:

The Minimum Capacity st Cut Problem (MinCut) is an intensively studied problem in combinatorial optimization. A natural extension is the problem of choosing a minimum capacity st cut when arc capacities are unknown but confined to known intervals. This motivates the Robust Minimum Capacity st Cut Problem (RobuCut), which has applications such as open‐pit mining and project scheduling. In this paper, we show how RobuCut can be reduced to solving a sequence of maximum flow problems and provide an efficient algorithm for rapidly solving this sequence of problems. We demonstrate that our algorithm solves instances of RobuCut in seconds that would require hours if a standard maximum flow solver is iteratively used as a black‐box subroutine.

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