Competitive Online Multicommodity Routing

  • Tobias Harks
  • Stefan Heinz
  • Marc E. Pfetsch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4368)


In this paper we study online multicommodity minimum cost routing problems in networks, where commodities have to be routed sequentially. The flow of each commodity can be split on several paths. Arcs are equipped with load dependent price functions defining routing costs. We discuss a greedy online algorithm that routes each commodity by minimizing a convex cost function that only depends on the demands previously routed. We present a competitive analysis of this algorithm showing that for affine linear price functions this algorithm is \(\tfrac{4K}{2+K}\)-competitive, where K is the number of commodities. For the parallel arc case, this algorithm is optimal. Without restrictions on the price functions and network, no algorithm is competitive. Finally, we investigate a variant in which the demands have to be routed unsplittably.


Competitive Ratio Online Algorithm Single Path Price Function Competitive Analysis 
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 2007

Authors and Affiliations

  • Tobias Harks
    • 1
  • Stefan Heinz
    • 1
  • Marc E. Pfetsch
    • 1
  1. 1.Konrad-Zuse-Zentrum für Informationstechnik BerlinBerlinGermany

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