Experimental evaluation of parametric max-flow algorithms

Maxim Babenko, Jonathan Derryberry, Andrew Goldberg, Robert Tarjan, Yunhong Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

The parametric maximum flow problem is an extension of the classical maximum flow problem in which the capacities of certain arcs are not fixed but are functions of a single parameter. Gallo et al. [6] showed that certain versions of the push-relabel algorithm for ordinary maximum flow can be extended to the parametric problem while only increasing the worst-case time bound by a constant factor. Recently Zhang et al. [14,13] proposed a novel, simple balancing algorithm for the parametric problem on bipartite networks. They claimed good performance for their algorithm on networks arising from a real-world application. We describe the results of an experimental study comparing the performance of the balancing algorithm, the GGT algorithm, and a simplified version of the GGT algorithm, on networks related to those of the application of Zhang et al. as well as networks designed to be hard for the balancing algorithm. Our implementation of the balancing algorithm beats both versions of the GGT algorithm on networks related to the application, thus supporting the observations of Zhang et al. On the other hand, the GGT algorithm is more robust; it beats the balancing algorithm on some natural networks, and by asymptotically increasing amount on networks designed to be hard for the balancing algorithm.

Original languageEnglish (US)
Title of host publicationExperimental Algorithms - 6th International Workshop, WEA 2007, Proceedings
PublisherSpringer Verlag
Pages256-269
Number of pages14
ISBN (Print)3540728449, 9783540728443
DOIs
StatePublished - 2007
Event6th International Workshop on Experimental Algorithms, WEA 2007 - Rome, Italy
Duration: Jun 6 2007Jun 8 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4525 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Workshop on Experimental Algorithms, WEA 2007
CountryItaly
CityRome
Period6/6/076/8/07

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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