A Network Analysis of Genetic Algorithms(Biocybernetics, Neurocomputing)

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概要

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• In recent years, network analysis has revealed that some real networks have the properties of small-world and/or scale-free networks. In this study, 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 (CPL), which is one of the most popular criteria in small-world networks, is derived analytically and shows how much the crossover operation affects the path length between two populations. As a result, the crossover operation is not so useful for shortening the CPL.

• 社団法人電子情報通信学会の論文
• 2007-06-01

著者

• Ikeda Kazushi

  Kyoto Univ. Kyoto‐shi Jpn

• Ikeda Kazushi

  Kyoto University

• FUNAYA Hiroyuki

  Kyoto University

関連論文

• A Network Analysis of Genetic Algorithms(Biocybernetics, Neurocomputing)
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• Geometrical Properties of Lifting-Up in the Nu Support Vector Machines(Biocybernetics, Neurocomputing)

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