Crossover Operators to Control Size Growth in Linear GP and Variable Length GAs

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{Chu:2008:cec,
  author =       "Dominique Chu and Jonathan E. Rowe",
  title =        "Crossover Operators to Control Size Growth in Linear
                 {GP} and Variable Length {GA}s",
  booktitle =    "2008 IEEE World Congress on Computational
                 Intelligence",
  year =         "2008",
  editor =       "Jun Wang",
  address =      "Hong Kong",
  month =        "1-6 " # jun,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-1823-7",
  file =         "EC0096.pdf",
  abstract =     "In various nuances of evolutionary algorithms it has
                 been observed that variable sized genomes exhibit large
                 degrees of redundancy and corresponding undue growth.
                 This phenomenon is commonly referred to as ``bloat.''
                 The present contribution investigates the role of
                 crossover operators as the cause for length changes in
                 variable length genetic algorithms and linear GP. Three
                 crossover operators are defined; each is tested with
                 three different fitness functions. The aim of this
                 article is to indicate suitable designs of crossover
                 operators that allow efficient exploration of designs
                 of solutions of a wide variety of sizes, while at the
                 same time avoiding bloat.",
  keywords =     "genetic algorithms, genetic programming",
  notes =        "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
                 EPS and the IET.",
}

Genetic Programming entries for Dominique Chu Jonathan E Rowe