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Atavistic Strategy for Genetic Algorithm

  • Dongmei Lin
  • Xiaodong Li
  • Dong Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6728)

Abstract

Atavistic evolutionary strategy for genetic algorithm is put forward according to the atavistic phenomena existing in the process of biological evolution, and the framework of the new strategy is given also. The effectiveness analysis of the new strategy is discussed by three characteristics of the reproduction operators. The introduction of atavistic evolutionary strategy is highly compatible with the minimum induction pattern, and increases the population diversity to a certain extent. The experimental results show that the new strategy improves the performance of genetic algorithm on convergence time and solution quality.

Keywords

genetic algorithm atavistic evolutionary strategy atavistic operator atavistic probability premature convergence 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Dongmei Lin
    • 1
  • Xiaodong Li
    • 2
  • Dong Wang
    • 3
  1. 1.Center of Information and Education TechnologyFoshan UniversityFoshanChina
  2. 2.School of Computer Science and Information TechnologyRMIT UniversityMelbourneAustralia
  3. 3.Department of Computer Science and TechnologyFoshan UniversityFoshanChina

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