Variable size genetic network programming with binomial distribution

Bing Li, Xianneng Li, Shingo Mabu, Kotaro Hirasawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2011 IEEE Congress of Evolutionary Computation, CEC 2011
Pages973-980
Number of pages8
DOIs
Publication statusPublished - 2011
Event2011 IEEE Congress of Evolutionary Computation, CEC 2011 - New Orleans, LA
Duration: 2011 Jun 52011 Jun 8

Other

Other2011 IEEE Congress of Evolutionary Computation, CEC 2011
CityNew Orleans, LA
Period11/6/511/6/8

Keywords

  • Binomial probability distribution
  • Crossover
  • Genetic Network Programming
  • Tile-world
  • Variable size

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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  • Cite this

    Li, B., Li, X., Mabu, S., & Hirasawa, K. (2011). Variable size genetic network programming with binomial distribution. In 2011 IEEE Congress of Evolutionary Computation, CEC 2011 (pp. 973-980). [5949723] https://doi.org/10.1109/CEC.2011.5949723