Accelerating filtering techniques for numeric CSPs

  • Authors:
  • Yahia Lebbah;Olivier Lhomme

  • Affiliations:
  • Départment Informatique, Faculté des Sciences, Université d'Oran Es-Senia, B.P. 1524, El-M'Naouar Oran, Algeria;ILOG, 1681 route des Dolines, Valbonne, France

  • Venue:
  • Artificial Intelligence
  • Year:
  • 2002

Quantified Score

Hi-index 0.00

Visualization

Abstract

Search algorithms for solving Numeric CSPs (Constraint Satisfaction Problems) make an extensive use of filtering techniques. In this paper we show how those filtering techniques can be accelerated by discovering and exploiting some regularities during the filtering process. Two kinds of regularities are discussed, cyclic phenomena in the propagation queue and numeric regularities of the domains of the variables. We also present in this paper an attempt to unify numeric CSPs solving methods from two distinct communities, that of CSP in artificial intelligence, and that of interval analysis.