Liers, Frauke and Pardella, Gregor (2011). Simplifying Maximum Flow Computations: the Effect of Shrinking and Good Initial Flows. Discrete Applied Mathematics, 159 (17). 2187 -2203. Elsevier Science.

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Abstract

Maximum-flow problems occur in a wide range of applications. Although already well-studied, they are still an area of active research. The fastest available implementations for determining maximum flows in graphs are either based on augmenting-path or on push-relabel algorithms. In this work, we present two ingredients that, appropriately used, can considerably speed up these methods. On the theoretical side, we present flow-conserving conditions under which subgraphs can be contracted to a single vertex. These rules are in the same spirit as presented by Padberg and Rinaldi (Math. Programming (47), 1990) for the minimum cut problem in graphs. These rules allow the reduction of known worst-case instances for different maximum flow algorithms to equivalent trivial instances. On the practical side, we propose a two-step max-flow algorithm for solving the problem on instances coming from physics and computer vision. In the two-step algorithm flow is first sent along augmenting paths of restricted lengths only. Starting from this flow, the problem is then solved to optimality using some known max-flow methods. By extensive experiments on instances coming from applications in theoretical physics and in computer vision, we show that a suitable combination of the proposed techniques speeds up traditionally used methods.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Liers, FraukeUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pardella, GregorUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-550148
Journal or Publication Title: Discrete Applied Mathematics
Volume: 159
Number: 17
Page Range: 2187 -2203
Date: 2011
Publisher: Elsevier Science
Language: English
Faculty: Faculty of Mathematics and Natural Sciences
Divisions: Faculty of Mathematics and Natural Sciences > Department of Mathematics and Computer Science > Institute of Computer Science
Subjects: Data processing Computer science
Refereed: No
URI: http://kups.ub.uni-koeln.de/id/eprint/55014

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