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Evolving Variable-Ordering Heuristics for Constrained Optimisation

  • Stuart Bain
  • John Thornton
  • Abdul Sattar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3709)

Abstract

In this paper we present and evaluate an evolutionary approach for learning new constraint satisfaction algorithms, specifically for MAX-SAT optimisation problems. Our approach offers two significant advantages over existing methods: it allows the evolution of more complex combinations of heuristics, and; it can identify fruitful synergies among heuristics. Using four different classes of MAX-SAT problems, we experimentally demonstrate that algorithms evolved with this method exhibit superior performance in comparison to general purpose methods.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Stuart Bain
    • 1
  • John Thornton
    • 1
  • Abdul Sattar
    • 1
  1. 1.Institute for Integrated and Intelligent SystemsGriffith UniversityAustralia

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