A filtering algorithm for global sequencing constraints | SpringerLink
Skip to main content

A filtering algorithm for global sequencing constraints

  • Session 1
  • Conference paper
  • First Online:
Principles and Practice of Constraint Programming-CP97 (CP 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1330))

Abstract

Sequencing constraints have proved very useful in many real-life problems such as rostering or car sequencing problems. They are used to express constraints such as: every sequence of 7 days of work must contain at least 2 days off. More precisely, a global sequencing constraint (gsc) C is specified in terms of an ordered set of variables X (C) = {x 1,..., x p} which take their values in D(C) = {v 1,..., v d}, some integers q, min and max and a given subset V of D(C). On one hand, a gsc constrains the number of variables in X(C) instantiated to a value v i ε D(C) be in an interval [1 i, u i]. On the other hand, a gsc constrains for each sequence S i of q consecutive variables of X(C), that at least min and at most max variables of Si are instantiated to a value of V. In this paper, we propose an automatic reformulation of a gsc in terms of global cardinality constraints. This is equivalent to defining a powerful filtering algorithm for a gsc which deals with a part of the globality of the constraint. We illustrate the power of our approach on a set of difficult car sequencing problems.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. N. Beldiceanu and E. Contejean. Introducing global constraints in chip. Journal of Mathematical and Computer Modelling, 20(12):97–123, 1994.

    Google Scholar 

  2. M. Dincbas, H. Simonis, and P. Van Hentenryck. Solving the car-sequencing problem in constraint logic programming. In ECAI'88, proceedings of the European Conference on Artificial Intelligence, pages 290–295, 1988.

    Google Scholar 

  3. A.K. Mackworth. Consistency in networks of relations. Artificial Intelligence, 8:99–118, 1977.

    Google Scholar 

  4. W.P. Nuijten. Time and Resource Constrained Scheduling: A Constraint Satisfaction Approach. PhD thesis, Eindhoven University of Technology, 1994.

    Google Scholar 

  5. J-F. Puget and M. Leconte. Beyong the glass box: Constraints as objects. In John Lloyd, editor, Logic Programming, Proceedings of the 1995 International Symposium, pages 513–527. The MIT Press, Portland, Oregon, 1995.

    Google Scholar 

  6. J-C. Régin. A filtering algorithm for constraints of difference in CSPs. In AAAI-94, proceedings of the Twelth National Conference on Artificial Intelligence, pages 362–367, Seattle, Washington, 1994.

    Google Scholar 

  7. J-C. Régin. Generalized arc consistency for global cardinality constraint. In AAAI-96, proceedings of the Thirteenth National Conference on Artificial Intelligence, pages 209–215, Portland, Oregon, 1996.

    Google Scholar 

  8. H. Simonis. Problem classification scheme for finite domain constraint solving. In CP96, Workshop on Constraint Programming Applications: An Inventory and Taxonomy, pages 1–26, Cambridge, MA, USA, 1996.

    Google Scholar 

  9. B.M. Smith. Succeed-first or fail-first: A case study in variable and value ordering. In proceedings ILOG Solver and ILOG Scheduler Second International Users' Conference, Paris, France, 1996.

    Google Scholar 

  10. P. Van Hentenryck, Y. Deville, and C.M. Teng. A generic arc-consistency algorithm and its specializations. Artificial Intelligence, 57:291–321, 1992.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Gert Smolka

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Régin, JC., Puget, JF. (1997). A filtering algorithm for global sequencing constraints. In: Smolka, G. (eds) Principles and Practice of Constraint Programming-CP97. CP 1997. Lecture Notes in Computer Science, vol 1330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0017428

Download citation

  • DOI: https://doi.org/10.1007/BFb0017428

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63753-0

  • Online ISBN: 978-3-540-69642-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics