Mutagenesis as a Diversity Enhancer and Preserver in Evolution Strategies

  • José L. Guerrero
  • Alfonso Gómez-Jordana
  • Antonio Berlanga
  • José M. Molina
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 151)


Mutagenesis is a process which forces the coverage of certain zones of the search space during the generations of an evolution strategy, by keeping track of the covered ranges for the different variables in the so called gene matrix. Originally introduced as an artifact to control the automated stopping criterion in a memetic algorithm, ESLAT, it also improved the exploration capabilities of the algorithm, even though this was considered a secondary matter and not properly analyzed or tested. This work focuses on this diversity enhancement, redefining mutagenesis to increase this characteristic, measuring this improvement over a set of twenty-seven unconstrained optimization functions to provide statistically significant results.


Search Space Evolution Strategy Gene Matrix Evolutionary Computation Memetic 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 2012

Authors and Affiliations

  • José L. Guerrero
    • 1
  • Alfonso Gómez-Jordana
    • 1
  • Antonio Berlanga
    • 1
  • José M. Molina
    • 1
  1. 1.Computer Science Department, Group of Applied Artificial Intelligence.University Carlos III of MadridMadridSpain

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