Population Implosion in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Sean Luke and Gabriel Catalin Balan and Liviu Panait",
  title =        "Population Implosion in Genetic Programming",
  booktitle =    "Genetic and Evolutionary Computation -- GECCO-2003",
  editor =       "E. Cant{\'u}-Paz and J. A. Foster and K. Deb and 
                 D. Davis and R. Roy and U.-M. O'Reilly and H.-G. Beyer and 
                 R. Standish and G. Kendall and S. Wilson and 
                 M. Harman and J. Wegener and D. Dasgupta and M. A. Potter and 
                 A. C. Schultz and K. Dowsland and N. Jonoska and 
                 J. Miller",
  year =         "2003",
  pages =        "1729--1739",
  address =      "Chicago",
  publisher_address = "Berlin",
  month =        "12-16 " # jul,
  volume =       "2724",
  series =       "LNCS",
  ISBN =         "3-540-40603-4",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://cs.gmu.edu/~lpanait/papers/luke03population.pdf",
  DOI =          "doi:10.1007/3-540-45110-2_65",
  abstract =     "With the exception of a small body of
                 adaptive-parameter literature, evolutionary computation
                 has traditionally favored keeping the population size
                 constant through the course of the run. Unfortunately,
                 genetic programming has an aging problem: for various
                 reasons, late in the run the technique become less
                 effective at optimization. Given a fixed number of
                 evaluations, allocating many of them late in the run
                 may thus not be a good strategy. In this paper we
                 experiment with gradually decreasing the population
                 size throughout a genetic programming run, in order to
                 reallocate more evaluations to early generations. Our
                 results show that over four problem domains and three
                 different numbers of evaluations, decreasing the
                 population size is always as good as, and frequently
                 better than, various fixed-sized population
  notes =        "GECCO-2003. A joint meeting of the twelfth
                 International Conference on Genetic Algorithms
                 (ICGA-2003) and the eighth Annual Genetic Programming
                 Conference (GP-2003)",

Genetic Programming entries for Sean Luke Gabriel Catalin Balan Liviu Panait