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A Faster Strongly Polynomial Minimum Cost Flow Algorithm

Published: 01 April 1993 Publication History
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  • Abstract

    In this paper, we present a new strongly polynomial time algorithm for the minimum cost flow problem, based on a refinement of the Edmonds-Karp scaling technique. Our algorithm solves the uncapacitated minimum cost flow problem as a sequence of On log n shortest path problems on networks with n nodes and m arcs and runs in On log nm + n log n time. Using a standard transformation, this approach yields an Om log nm + n log n algorithm for the capacitated minimum cost flow problem. This algorithm improves the best previous strongly polynomial time algorithm, due to Z. Galil and E. Tardos, by a factor of n2/m. Our algorithm for the capacitated minimum cost flow problem is even more efficient if the number of arcs with finite upper bounds, say m', is much less than m. In this case, the running time of the algorithm is Om' + n log nm + n log n.

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    Published In

    cover image Operations Research
    Operations Research  Volume 41, Issue 2
    April 1993
    192 pages

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    INFORMS

    Linthicum, MD, United States

    Publication History

    Published: 01 April 1993

    Author Tags

    1. flow algorithms: a faster strongly polynomial minimum cost flow algorithm
    2. networks/graphs

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    • (2023)A Strongly Polynomial Algorithm for Approximate Forster Transforms and Its Application to Halfspace LearningProceedings of the 55th Annual ACM Symposium on Theory of Computing10.1145/3564246.3585191(1741-1754)Online publication date: 2-Jun-2023
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