Tuning Selection Pressure in Tournament Selection

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@TechReport{Xie:tr09-10,
  author =       "Huayang Xie and Mengjie Zhang",
  title =        "Tuning Selection Pressure in Tournament Selection",
  institution =  "School of Engineering and Computer Science. Victoria
                 University of Wellington",
  year =         "2009",
  number =       "ECSTR-09-10",
  address =      "New Zealand",
  keywords =     "genetic algorithms, genetic programming, Tournament
                 Selection, Selection Pressure, Tuning Strategy",
  URL =          "http://ecs.victoria.ac.nz/twiki/pub/Main/TechnicalReportSeries/ECSTR09-10.pdf",
  abstract =     "Selection pressure controls the selection of
                 individuals from the current population to produce a
                 new population in the next generation. It gives
                 individuals of higher quality a higher probability of
                 being used to create the next generation so that
                 Evolutionary Algorithms (EAs) can focus on promising
                 regions in the search space. An evolutionary learning
                 process is dynamic and requires different selection
                 pressures at different learning stages in order to
                 speed up convergence or avoid local optima. Therefore,
                 it desires selection mechanisms being able to
                 automatically tune selection pressure during evolution.
                 Tournament selection is a popular selection method in
                 EAs. This paper focuses on tournament selection and
                 shows that standard tournament selection is unaware of
                 the dynamics in the evolutionary process thus is unable
                 to tune selection pressure automatically. This paper
                 then presents a novel approach which integrates the
                 knowledge of the Fitness Rank Distribution (FRD) of a
                 population into tournament selection. Through
                 mathematical modelling, simulations and experimental
                 study, this paper shows that the new approach is
                 effective and using the knowledge of FRD is a promising
                 way to modify the standard tournament selection method
                 for tuning the selection pressure dynamically and
                 automatically along evolution.",
  size =         "14 pages",
}

Genetic Programming entries for Huayang Jason Xie Mengjie Zhang

Citations