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A fast algorithm for the generalized parametric minimum cut problem and applications

Published: 01 June 1992 Publication History

Abstract

Many combinatorial optimization problems are solved by a sequence of network flow computations on a network whose edge capacities are given as a function of a parameter λ. Recently Galloet al. [7] made a major advance in solving such parametric flow problems. They showed that for an important class of networks, calledmonotone parametric flow networks, a sequence ofO(n) flow computations could be solved in the same worst-case time bound as a single flow. However, these results require one of two special assumptions: either that the λ values are presented in increasing or decreasing order; or that the edge capacity functions are affine functions of λ. In this paper we show how to remove both of these assumptions while obtaining the same running times as in [7]. This observation generalizes and unifies the two major results of [7], and allows its ideas to be applied to many new combinatorial problems. Of greatest importance, it allows the efficient application of binary search and successive binary search to a sequence of network flow problems.

References

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Cited By

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  • (2010)Optimal web-scale tiering as a flow problemProceedings of the 24th International Conference on Neural Information Processing Systems - Volume 110.5555/2997189.2997338(1333-1341)Online publication date: 6-Dec-2010

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Published In

cover image Algorithmica
Algorithmica  Volume 7, Issue 1-6
Jun 1992
628 pages

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 June 1992
Revision received: 07 June 1990
Received: 18 August 1988

Author Tags

  1. Graph algorithms
  2. Combinatorial optimization
  3. Network flow
  4. Parametric optimization

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View all
  • (2010)Optimal web-scale tiering as a flow problemProceedings of the 24th International Conference on Neural Information Processing Systems - Volume 110.5555/2997189.2997338(1333-1341)Online publication date: 6-Dec-2010

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