Population variation in genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Peyman Kouchakpour and Anthony Zaknich and 
                 Thomas Braunl",
  title =        "Population variation in genetic programming",
  journal =      "Information Sciences",
  year =         "2007",
  volume =       "177",
  number =       "17",
  pages =        "3438--3452",
  month =        "1 " # sep,
  keywords =     "genetic algorithms, genetic programming, Computational
                 effort, Average number of evaluations, Convergence,
                 Population variation",
  DOI =          "doi:10.1016/j.ins.2007.02.032",
  abstract =     "A new population variation approach is proposed,
                 whereby the size of the population is systematically
                 varied during the execution of the genetic programming
                 process with the aim of reducing the computational
                 effort compared with standard genetic programming
                 (SGP). Various schemes for altering population size
                 under this proposal are investigated using a
                 comprehensive range of standard problems to determine
                 whether the nature of the population variation, i.e.
                 the way the population is varied during the search, has
                 any significant impact on GP performance. The initial
                 population size is varied in relation to the initial
                 population size of the SGP such that the worst case
                 computational effort is never greater than that of the
                 SGP. It is subsequently shown that the proposed
                 population variation schemes do have the capacity to
                 provide solutions at a lower computational cost
                 compared with the SGP.",

Genetic Programming entries for Peyman Kouchakpour Anthony Zaknich Thomas Braunl