Extending the GA-EDA Hybrid Algorithm to Study Diversification and Intensification in GAs and EDAs

  • V. Robles
  • J. M. Peña
  • M. S. Pérez
  • P. Herrero
  • O. Cubo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3646)


Hybrid metaheuristics have received considerable interest in recent years. Since several years ago, a wide variety of hybrid approaches have been proposed in the literature including the new GA-EDA approach. We have design and implemented an extension to this GA-EDA approach, based on statistical significance tests. This approach had allowed us to make an study of the balance of diversification (exploration) and intensification (exploitation) in Genetic Algorithms and Estimation of Distribution Algorithms.


Local Search Hybrid Algorithm Distribution Algorithm Participation Ratio Hybrid Evolutionary Algorithm 
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 2005

Authors and Affiliations

  • V. Robles
    • 1
  • J. M. Peña
    • 1
  • M. S. Pérez
    • 1
  • P. Herrero
    • 2
  • O. Cubo
    • 1
  1. 1.Departamento de Arquitectura y Tecnología de Sistemas InformáticosUniversidad Politécnica de MadridMadridSpain
  2. 2.Departamento de Lenguajes y SistemasUniversidad Politécnica de MadridMadridSpain

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