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Conflict Directed Lazy Decomposition

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Book cover Principles and Practice of Constraint Programming (CP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7514))

Abstract

Two competing approaches to handling complex constraints in satisfaction and optimization problems using SAT and LCG/SMT technology are: decompose the complex constraint into a set of clauses; or (theory) propagate the complex constraint using a standalone algorithm and explain the propagation. Each approach has its benefits. The decomposition approach is prone to an explosion in size to represent the problem, while the propagation approach may require exponentially more search since it does not have access to intermediate literals for explanation. In this paper we show how we can obtain the best of both worlds by lazily decomposing a complex constraint propagator using conflicts to direct it. If intermediate literals are not helpful for conflicts then it will act like the propagation approach, but if they are helpful it will act like the decomposition approach. Experimental results show that it is never much worse than the better of the decomposition and propagation approaches, and sometimes better than both.

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Author information

Authors and Affiliations

  1. Technical University of Catalonia (UPC), Barcelona, Spain

    Ignasi Abío

  2. Department of Computing and Information Systems, and NICTA Victoria Laboratory, The University of Melbourne, Australia

    Peter J. Stuckey

Authors
  1. Ignasi Abío
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  2. Peter J. Stuckey
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Editor information

Editors and Affiliations

  1. DEIS Universitá di Bologna, V.le Risorgimento, 2, 40136, Bologna, Italy

    Michela Milano

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Abío, I., Stuckey, P.J. (2012). Conflict Directed Lazy Decomposition. In: Milano, M. (eds) Principles and Practice of Constraint Programming. CP 2012. Lecture Notes in Computer Science, vol 7514. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33558-7_8

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  • DOI: https://doi.org/10.1007/978-3-642-33558-7_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33557-0

  • Online ISBN: 978-3-642-33558-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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