A filtering algorithm for global sequencing constraints

  • Jean-Charles Régin
  • Jean-François Puget
Session 1
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1330)


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) = {x1,..., xp} which take their values in D(C) = {v1,..., vd}, 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 vi ε D(C) be in an interval [1i, ui]. On the other hand, a gsc constrains for each sequence Si 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.


Assembly Line Constraint Satisfaction Problem Constraint Network Implied Constraint Backtrack Algorithm 
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 1997

Authors and Affiliations

  • Jean-Charles Régin
    • 1
  • Jean-François Puget
    • 1
  1. 1.ILOG S.A.Gentilly CedexFrance

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