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2007
Springer

Experimental Evaluation of Parametric Max-Flow Algorithms

9 years 1 months ago
Experimental Evaluation of Parametric Max-Flow Algorithms
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...
Maxim A. Babenko, Jonathan Derryberry, Andrew V. G
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where WEA
Authors Maxim A. Babenko, Jonathan Derryberry, Andrew V. Goldberg, Robert Endre Tarjan, Yunhong Zhou
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