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Yet Another Local Search Method for Constraint Solving

  • Philippe Codognet
  • Daniel Diaz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2264)

Abstract

We propose a generic, domain-independent local search method called adaptive search for solving Constraint Satisfaction Problems (CSP). We design a new heuristics that takes advantage of the structure of the problem in terms of constraints and variables and can guide the search more precisely than a global cost function to optimize (such as for instance the number of violated constraints). We also use an adaptive memory in the spirit of Tabu Search in order to prevent stagnation in local minima and loops. This method is generic, can apply to a large class of constraints (e.g. linear and non-linear arithmetic constraints, symbolic constraints, etc) and naturally copes with over-constrained problems. Preliminary results on some classical CSP problems show very encouraging performances.

Keywords

Local search constraint solving combinatorial optimization search algorithms 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Philippe Codognet
    • 1
  • Daniel Diaz
    • 2
  1. 1.LIP6University of Paris 6ParisFRANCE
  2. 2.CRIUniversity of Paris IParis Cedex 13FRANCE

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