Skip to main content

From Declarative Set Constraint Models to “Good” SAT Instances

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8884))

Abstract

On the one hand, Constraint Satisfaction Problems allow one to declaratively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to declaratively model set constraint problems, to reduce them, and to encode them into ”good” SAT instances. We illustrate our technique on the well-known nqueens problem. Our technique is simpler, more expressive, and less error-prone than direct hand modeling. The SAT instances that we automatically generate are rather small w.r.t. hand-written instances.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Choco, http://www.emn.fr/z-info/choco-solver/

  2. Apt, K.: Principles of Constraint Programming. Cambridge University Press (2003)

    Google Scholar 

  3. Bacchus, F.: Gac via unit propagation. In: Bessière, C. (ed.) CP 2007. LNCS, vol. 4741, pp. 133–147. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  4. Bailleux, O., Boufkhad, Y.: Efficient CNF encoding of boolean cardinality constraints. In: Rossi, F. (ed.) CP 2003. LNCS, vol. 2833, pp. 108–122. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  5. Bessière, C., Hebrard, E., Walsh, T.: Local consistencies in SAT. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 299–314. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  6. Eén, N., Sörensson, N.: An extensible sat-solver. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 502–518. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  7. Früwirth, T.: Constraint Handling Rules. Cambridge University Press (2009)

    Google Scholar 

  8. Garey, M.R., Johnson, D.S.: Computers and Intractability, A Guide to the Theory of NP-Completeness. W.H. Freeman & Company (1979)

    Google Scholar 

  9. Gent, I., Lynce, I.: A sat encoding for the social golfer problem. In: IJCAI 2005 Workshop on Modelling and Solving Problems with Constraints (2005)

    Google Scholar 

  10. Gervet, C.: Conjunto: Constraint propagation over set constraints with finite set domain variables. In: Proc. of ICLP 1994, p. 733. MIT Press (1994)

    Google Scholar 

  11. Lardeux, F., Monfroy, E., Crawford, B., Soto, R.: Set constraint model and automated encoding into sat: Application to the social golfer problem. Submitted to Annals of Operations Research

    Google Scholar 

  12. Lardeux, F., Monfroy, E., Saubion, F., Crawford, B., Castro, C.: SAT encoding and CSP reduction for interconnected alldiff constraints. In: Aguirre, A.H., Borja, R.M., Garciá, C.A.R. (eds.) MICAI 2009. LNCS, vol. 5845, pp. 360–371. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  13. Legeard, B., Legros, E.: Short overview of the CLPS system. In: Małuszyński, J., Wirsing, M. (eds.) PLILP 1991. LNCS, vol. 528, pp. 431–433. Springer, Heidelberg (1991)

    Chapter  Google Scholar 

  14. Mackworth, A.: Encyclopedia on Artificial Intelligence, chapter Constraint Satisfaction. John Wiley (1987)

    Google Scholar 

  15. Monfroy, E.: A coordination-based chaotic iteration algorithm for constraint propagation. In: Proc of ACM SAC 2000 (1), pp. 262–269. ACM (2000)

    Google Scholar 

  16. Monfroy, E., Saubion, F., Lambert, T.: On hybridization of local search and constraint propagation. In: Demoen, B., Lifschitz, V. (eds.) ICLP 2004. LNCS, vol. 3132, pp. 299–313. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  17. Prestwich, S., Roli, A.: Symmetry breaking and local search spaces. In: Barták, R., Milano, M. (eds.) CPAIOR 2005. LNCS, vol. 3524, pp. 273–287. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  18. Rossi, F., van Beek, P., Walsh, T. (eds.): Handbook of Constraint Programming. Elsevier (2006)

    Google Scholar 

  19. Triska, M., Musliu, N.: An improved sat formulation for the social golfer problem. Annals of Operations Research 194(1), 427–438 (2012)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Lardeux, F., Monfroy, E. (2014). From Declarative Set Constraint Models to “Good” SAT Instances. In: Aranda-Corral, G.A., Calmet, J., Martín-Mateos, F.J. (eds) Artificial Intelligence and Symbolic Computation. AISC 2014. Lecture Notes in Computer Science(), vol 8884. Springer, Cham. https://doi.org/10.1007/978-3-319-13770-4_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-13770-4_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13769-8

  • Online ISBN: 978-3-319-13770-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics