Generalized max flows and augmenting paths

  • David Hartvigsen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 920)


It is well-known that if augmenting paths are used to solve a max flow problem then two problems can arise: 1) the number of augmenting paths needed can depend on the size of the capacities; and 2) if the capacities are irrational then the algorithm need not even converge to an optimal solution. Edmonds and Karp [4] and Dinic [3] were the first to show that these problems can be overcome using minimum length augmenting paths. In this paper we examine to what extent augmenting paths and the results of Edmonds and Karp can be generalized. In particular, we consider these ideas for the following generalized max flow problem (first studied by Fulkerson [7]): maxx1:Ax=0,0≤xc.


Feasible Solution Flow Problem Polynomial Algorithm Independent Column Proportional Flow 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • David Hartvigsen
    • 1
  1. 1.Department of Management, College of Business AdministrationUniversity of Notre DameNotre Dame

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