Analysis of crossover rate in variable size Genetic Network Programming with binomial distribution

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

*Corresponding author for this work

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


Variable Size Genetic Network Programming (GNPvs) with Binomial Distribution is a new type of Genetic Network Programming, which permits the individuals with variable size and obtains the optimal size of individuals during evolution. In contrast to swapping the corresponding nodes in the crossover of Genetic Network Programming (GNP), the crossover of GNPvs moves a number of nodes from each parent individual to another parent individual. The probability of selecting the number of nodes to move satisfies the binomial distribution, which is controls by the crossover rate and the initial size of the individuals. In this paper, the performance of the algorithm and the size of the individuals are studied by changing the most important parameter, i.e., crossover rate. Since GNPvs may suffer from the bloating problem, the Island Model is introduced to control the size of the individuals implicitly. The well-known test bed Tileworld is used to show the numeric results in the simulations.

Original languageEnglish
Title of host publicationProceedings of the SICE Annual Conference
Number of pages6
Publication statusPublished - 2011
Event50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 - Tokyo, Japan
Duration: 2011 Sept 132011 Sept 18


Other50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011


  • Binomial distribution
  • Bloating problem
  • Crossover
  • Genetic Network Programming
  • Variable size

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications

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