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Representative Selection for Cooperative Co-evolutionary Genetic Algorithms

  • Sun Xiao-yan
  • Gong Dun-wei
  • Hao Guo-sheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4247)

Abstract

The performance of cooperative co-evolutionary genetic algorithms is highly affected by the representative selection strategy. But rational method is absent now. Oriented to the shortage, the representative selection strategy is studied based on the parallel implementation of cooperative co-evolutionary genetic algorithms in LAN. Firstly, the active cooperation ideology for representative selection and the dynamical determinate method on cooperation pool size are put forward. The methods for determining cooperation pool size, selecting cooperators and permuting cooperations are presented based on the evolutionary ability of sub-population and distributive performance of the individuals. Thirdly, the implementation steps are given. Lastly, the results of benchmark functions optimization show the validation of the method.

Keywords

Parallel Implementation Evolutionary Competence Representative Selection Cooperative Coevolution Evolutionary Ability 
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

  • Sun Xiao-yan
    • 1
  • Gong Dun-wei
    • 1
  • Hao Guo-sheng
    • 1
  1. 1.School of Information and Electrical EngineeringChina University of Mining & Technology XuzhouJiangsuChina

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