• DocumentCode
    2218201
  • Title

    Variable Size Genetic Network Programming with Binomial Distribution

  • Author

    Li, Bing ; Li, Xianneng ; Mabu, Shingo ; Hirasawa, Kotaro

  • Author_Institution
    Grad. Sch. of Inf., Waseda Univ., Kitakyushu, Japan
  • fYear
    2011
  • fDate
    5-8 June 2011
  • Firstpage
    973
  • Lastpage
    980
  • Abstract
    This paper proposes a different type of Genetic Network Programming (GNP) Variable Size Genetic Network Programming (GNPvs) with Binomial Distribution. In contrast to the individuals with fixed size in Standard GNP, GNPvs will change the size of the individuals and obtain the optimal size of them during evolution. The proposed method defines a new type of crossover to implement the new feature of GNP. The new crossover will select the number of nodes to move from each parent GNP to another parent GNP. The probability of selecting the number of nodes to move satisfies the binomial probability distribution. The proposed method can keep the effectiveness of crossover and improve the performance of GNP. In order to verify the performance of the proposed method, a well-known benchmark problem Tile-world is used in the simulations. The simulation results show the effectiveness of the proposed method.
  • Keywords
    algorithm theory; binomial distribution; genetic algorithms; binomial probability distribution; simulation; tile-world; variable size genetic network programming; Biological cells; Economic indicators; Genetic algorithms; Genetics; Probability distribution; Programming; Tiles; Binomial probability distribution; Crossover; Genetic Network Programming; Tile-world; Variable size;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2011 IEEE Congress on
  • Conference_Location
    New Orleans, LA
  • ISSN
    Pending
  • Print_ISBN
    978-1-4244-7834-7
  • Type

    conf

  • DOI
    10.1109/CEC.2011.5949723
  • Filename
    5949723