An Empirical Study of Multipopulation Genetic Programming

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@Article{Fernandez:2003:GPEM,
  author =       "Francisco Fernandez and Marco Tomassini and 
                 Leonardo Vanneschi",
  title =        "An Empirical Study of Multipopulation Genetic
                 Programming",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2003",
  volume =       "4",
  number =       "1",
  pages =        "21--51",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, distributed
                 evolutionary algorithms, parallel algorithms,
                 structured populations",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1023/A:1021873026259",
  abstract =     "This paper presents an experimental study of
                 distributed multipopulation genetic programming. Using
                 three well-known benchmark problems and one real-life
                 problem, we discuss the role of the parameters that
                 characterise the evolutionary process of standard
                 panmictic and parallel genetic programming. We find
                 that distributing individuals between subpopulations
                 offers in all cases studied here an advantage both in
                 terms of the quality of solutions and of the
                 computational effort spent, when compared to single
                 populations. We also study the influence of
                 communication patterns such as the communication
                 topology, the number of individuals exchanged and the
                 frequency of exchange on the evolutionary process. We
                 empirically show that the topology does not have a
                 marked influence on the results for the test cases
                 studied here, while the frequency and number of
                 individuals exchanged are related and there exists a
                 suitable range for those parameters which is
                 consistently similar for all the problems studied.",
  notes =        "Article ID: 5113071",
}

Genetic Programming entries for Francisco Fernandez de Vega Marco Tomassini Leonardo Vanneschi

Citations