An efficient generic network flow constraint

  • Authors:

  • Robin Steiger;Willem-Jan van Hoeve;Radosław Szymanek

  • Affiliations:

  • Fédérale de Lausanne, Lausanne, Switzerland;Carnegie Mellon University, Pittsburgh, PA;Fédérale de Lausanne, Lausanne, Switzerland

  • Venue:
  • Proceedings of the 2011 ACM Symposium on Applied Computing
  • Year:
  • 2011

  • Explaining flow-based propagation

    CPAIOR'12 Proceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

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Abstract

We propose a generic global constraint that can be applied to model a wide range of network flow problems using constraint programming. In our approach, all key aspects of a network flow can be represented by finite domain variables, making the constraint very expressive. At the same time, we utilize a network simplex algorithm to design a highly efficient, and incremental, domain filtering algorithm. We thus integrate two powerful techniques for discrete optimization: constraint programming and the network simplex algorithm. Our generic constraint can be applied to automatically implement effective and efficient domain filterng algorithms for ad-hoc networks, but also for existing global constraints that rely on a network structure, including several soft global constraints many of which are not yet supported by CP systems. Our experimental results demonstrate the efficiency of our constraint, that can achieve speed-ups of several orders of magnitude with negligible overhead, when compared to a decomposition into primitive constraints.