Lazy clause generation is a powerful approach to reducing search in constraint programming. For use in a lazy clause generation solver, global constraints must be extended to explain themselves. In this paper we present two new generic flow-based propagators (for hard and soft flow-based constraints) with several novel features, and most importantly, the addition of explanation capability. We discuss how explanations change the tradeoffs for propagation compared with the previous generic flow-based propagator, and show that the generic propagators can efficiently replace specialized versions, in particular for gcc and sequence constraints. Using real-world scheduling and rostering problems as examples, we compare against a number of standard Constraint Programming implementations of these contraints (and in the case of soft constraints, Mixed-Integer Programming models) to show that the new global propagators are extremely beneficial on these benchmarks.


Constraint Program Soft Constraint Global Constraint Nurse Rostering Residual Graph 
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 2012

Authors and Affiliations

  • Nicholas Downing
    • 1
  • Thibaut Feydy
    • 1
  • Peter J. Stuckey
    • 1
  1. 1.National ICT Australia and The University of MelbourneAustralia

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