Genetic programming with one-point crossover and subtree mutation for effective problem solving and bloat control

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Leonardo Trujillo",
  title =        "Genetic programming with one-point crossover and
                 subtree mutation for effective problem solving and
                 bloat control",
  journal =      "Soft Computing - A Fusion of Foundations,
                 Methodologies and Applications",
  year =         "2011",
  volume =       "15",
  number =       "8",
  pages =        "1551--1567",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming",
  publisher =    "Springer Berlin / Heidelberg",
  ISSN =         "1432-7643",
  DOI =          "doi:10.1007/s00500-010-0687-7",
  abstract =     "Genetic programming (GP) is one of the most widely
                 used paradigms of evolutionary computation due to its
                 ability to automatically synthesise computer programs
                 and mathematical expressions. However, because GP uses
                 a variable length representation, the individuals
                 within the evolving population tend to grow rapidly
                 without a corresponding return in fitness improvement,
                 a phenomenon known as bloat. In this paper, we present
                 a simple bloat control strategy for standard tree-based
                 GP that achieves a one order of magnitude reduction in
                 bloat when compared with standard GP on benchmark
                 tests, and practically eliminates bloat on two
                 real-world problems. Our proposal is to substitute
                 standard subtree crossover with the one-point crossover
                 (OPX) developed by Poli and Langdon (Second online
                 world conference on soft computing in engineering
                 design and manufacturing, Springer, Berlin ( 1997 ))
                 \cite{poli:1997:1pxoWSC2c}, while maintaining all other
                 GP aspects standard, particularly subtree mutation. OPX
                 was proposed for theoretical purposes related to GP
                 schema theorems, however since it curtails exploration
                 during the search it has never achieved widespread use.
                 In our results, on the other hand, we are able to show
                 that OPX can indeed perform an effective search if it
                 is coupled with subtree mutation, thus combining the
                 bloat control capabilities of OPX with the exploration
                 provided by standard mutation.",
  affiliation =  "Instituto Tecnologico de Tijuana, Av. Tecnologico S/N,
                 Fracc. Tomas Aquino, Tijuana, BC, Mexico",

Genetic Programming entries for Leonardo Trujillo