Evolving Algorithms for Constraint Satisfaction

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  title =        "Evolving Algorithms for Constraint Satisfaction",
  author =       "Stuart Bain and John Thornton and Abdul Sattar",
  pages =        "265--272",
  booktitle =    "Proceedings of the 2004 IEEE Congress on Evolutionary
  year =         "2004",
  publisher =    "IEEE Press",
  month =        "20-23 " # jun,
  address =      "Portland, Oregon",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, Combinatorial
                 \& numerical optimization",
  URL =          "http://stuart.multics.org/publications/CEC2004.pdf",
  DOI =          "doi:10.1109/CEC.2004.1330866",
  size =         "8 pages",
  abstract =     "This paper proposes a framework for automatically
                 evolving constraint satisfaction algorithms using
                 genetic programming. The aim is to overcome the
                 difficulties associated with matching algorithms to
                 specific constraint satisfaction problems. A
                 representation is introduced that is suitable for
                 genetic programming and that can handle both complete
                 and local search heuristics. In addition, the
                 representation is shown to have considerably more
                 flexibility than existing alternatives, being able to
                 discover entirely new heuristics and to exploit
                 synergies between heuristics. In a preliminary
                 empirical study it is shown that the new framework is
                 capable of evolving algorithms for solving the
                 well-studied problem of boolean satisfiability
  notes =        "CEC 2004 - A joint meeting of the IEEE, the EPS, and
                 the IEE.",

Genetic Programming entries for Stuart Bain John Thornton Abdul Sattar