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Wolbachia Infection Improves Genetic Algorithms as Optimization Procedure

  • Mauricio Guevara-Souza
  • Edgar E. Vallejo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7505)

Abstract

This paper shows how the addition of Wolbachia infection can improve evolutionary function optimization by preventing the system from sticking at local optima. Firstly a variant of genetic algorithms that allows the introduction of Wolbachia is described. Then an application of this system to the optimization of a collection of mutimodal functions is described. Finally, we show how the introduction of Wolbachia infection improves the procedure in terms of both fitness and the number of generations required to obtain the solutions.

Keywords

Wolbachia function optimization genetic algorithms 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mauricio Guevara-Souza
    • 1
  • Edgar E. Vallejo
    • 1
  1. 1.Computer Science DepartmentTecnológico de Monterrey, Campus Estado de MéxicoMéxico

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