On Properties of Genetic Operators from a Network Analytical Viewpoint

  • Hiroyuki Funaya
  • Kazushi Ikeda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)


In recent years, network analysis has revealed that some real networks have the properties of small-world and/or scale-free networks. In this paper, a simple Genetic Algorithm (GA) is regarded as a network where each node and each edge respectively represent a population and the possibility of the transition between two nodes. The characteristic path length, which is one of the most popular criterion in small-world networks, is derived analytically. The results show how the crossover operation works in GAs to shorten the path length between two populations, compared to the length of the network with the mutation operation.


Genetic Algorithm Binary Sequence Genetic Operator Markov Chain Model Mutation Operation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hiroyuki Funaya
    • 1
  • Kazushi Ikeda
    • 1
  1. 1.Department of SystemsKyoto UniversityKyotoJapan

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