Evolving graph-based chromosome by means of variable size genetic network programming with binomial distribution

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@Article{Li:2013:TEEEb,
  author =       "Bing Li and Xianneng Li and Shingo Mabu and 
                 Kotaro Hirasawa",
  title =        "Evolving graph-based chromosome by means of variable
                 size genetic network programming with binomial
                 distribution",
  journal =      "IEEJ Transactions on Electrical and Electronic
                 Engineering",
  year =         "2013",
  volume =       "8",
  number =       "4",
  pages =        "348--356",
  month =        jul,
  publisher =    "Wiley",
  keywords =     "genetic algorithms, genetic programming, variable
                 size, genetic network programming, crossover, binomial
                 distribution, Tileworld",
  ISSN =         "1931-4981",
  DOI =          "doi:10.1002/tee.21865",
  size =         "9 pages",
  abstract =     "Genetic network programming (GNP) is a graph-based
                 evolutionary algorithm with fixed size, which has been
                 proven to solve complicated problems efficiently and
                 effectively. In this paper, variable size genetic
                 network programming (GNPvs) with binomial distribution
                 has been proposed, which will change the size of the
                 individuals and obtain their optimal size during
                 evolution. The proposed method will select the number
                 of nodes to move from one parent GNP to another parent
                 GNP during crossover to implement the new feature of
                 GNP. The probability of selecting the number of nodes
                 to move satisfies a binomial distribution. The proposed
                 method can keep the effectiveness of crossover, improve
                 the performance of GNP, and find the optimal size of
                 the individuals. The well-known testbed Tileworld is
                 used to show the numerical results in the
                 simulations.",
}

Genetic Programming entries for Bing Li Xianneng Li Shingo Mabu Kotaro Hirasawa

Citations