Advertisement

HIS: Hierarchical Solver for Over-Constrained Satisfaction Problems

  • Zerrin Yumak
  • Tatyana Yakhno
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3949)

Abstract

Constraint programming is an approach for solving mostly combinatorial problems by declaratively describing the problem and using special solving algorithms. Restrictions called constraints are stated over the problem variables that reduces the values each variable can take. In some cases it is not possible to satisfy all constraints or the user can state some preferences on them. One of the techniques to solve this kind of problems is modelling and solving the problem as a constraint hierarchy. This paper describes a hierarchical constraint solver HIS, which is developed in C++ using ILOG Solver as an ordinary constraint solver. HIS is based on refining algorithm. As an application a layout problem is considered.

Keywords

Constraint Satisfaction Constraint Satisfaction Problem Soft Constraint Hard Constraint Layout Problem 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bartak, R.: A Theoretical Framework for Constraint Hierarchy Solvers. In: Proceedings of the 15th European Conference on Artificial Intelligence, pp. 146–150. IOS Press, Amsterdam (2002)Google Scholar
  2. 2.
    Bartak, R.: Modeling Soft Constraints: A Survey. Charles University, Prague (2002)Google Scholar
  3. 3.
    Bistarelli, S., Codognet, P., Hui, H.K.C., Lee, J.H.M.: Solving Finite Domain Constraint Hierarchies by Local Consistency and Tree Search. In: Rossi, F. (ed.) CP 2003. LNCS, vol. 2833. Springer, Heidelberg (2003)Google Scholar
  4. 4.
    Borning, A., Duisberg, R., Freeman-Benson, B., Kramer, A., Woolf, M.: Constraint Hierarchies. In: Proceedings of the ACM Conference on Object Oriented Programming Systems, Languages and Applications, pp. 48–60 (1987)Google Scholar
  5. 5.
    Borning, A., Freeman-Benson, B.: Ultraviolet: A Constraint Satisfaction Algorithm for Interactive Graphics. Constraints 3(1), 9–32 (1998)CrossRefMATHGoogle Scholar
  6. 6.
    Freeman-Benson, B., Maloney, J., Borning, A.: An Incremental Constraint Solver. Communications of the ACM 33(1), 54–63 (1990)CrossRefGoogle Scholar
  7. 7.
    Freeman-Benson, B., Wilson, M., Borning, A.: DeltaStar: A General Algorithm for Incremental Constraint Satisfaction of Constraint Hierarchies. In: 11th Annual IEEE Phoenix Conference on Computers and Communications, pp. 561–568 (1992)Google Scholar
  8. 8.
    Freuder, E.C., Wallace, R.J.: Partial Constraint Satisfaction. Artificial Intelligence 58, 21–70 (1992)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Marriott, K., Stuckey, P.J.: Programming with Constraints: An Introduction. MIT Press, Cambridge (1998)MATHGoogle Scholar
  10. 10.
    Sannella, M.: The SkyBlue Constraint Solver and Its Applications. In: Proceedings of the First Workshop on Principles and Practice of Constraint Programming. MIT Press, Cambridge (1994)Google Scholar
  11. 11.
    Wilson, M., Borning, A.: Hierarchical Constraint Logic Programming. The Journal of Logic Programming Special Issue on Constraint Logic Programming 16, 227–318 (1993)MathSciNetMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zerrin Yumak
    • 1
  • Tatyana Yakhno
    • 1
  1. 1.Department of Computer EngineeringDokuz Eylul UniversityIzmirTurkey

Personalised recommendations