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Exploring Macroevolutionary Algorithms: Some Extensions and Improvements

  • J. A. Becerra
  • V. Díaz Casás
  • R. J. Duro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4507)

Abstract

Macroevolutionary Algorithms seem to work better than other Evolutionary Algorithms in problems characterized by having small populations where the evaluation of the individuals is computationally very expensive or is characterized by a very difficult search space with multiple narrow hyper-dimensional peaks and large areas between those peaks showing the same fitness value. This paper focuses on some aspects of Macroevolutionary Algorithms introducing some modifications that address weak points in the original algorithm, which are very relevant in some types of complex real world problems. All the modifications on the algorithm are tested in real world problems.

Keywords

Macroevolutionary Algorithms Evolutionary Algorithms 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • J. A. Becerra
    • 1
  • V. Díaz Casás
    • 1
  • R. J. Duro
    • 1
  1. 1.Grupo Integrado de Ingeniería, Universidade da CoruñaSpain

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