Real-Valued Genetic Algorithms with Disagreements

  • Andrei Lihu
  • Ştefan Holban
Part of the Studies in Computational Intelligence book series (SCI, volume 387)

Abstract

This paper introduces a new mutation operator for real-valued genetic algorithms that refines the evolutionary process using disagreements. After a short introduction, we describe the new concept theoretically and then we exemplify it by defining a Gaussian distribution-based disagreements operator: the 6σ-GAD. We transform two common real-valued genetic algorithms into their disagreements-enabled counterparts and we conduct several tests proving that our newly obtained algorithms perform better because they gain strengthened neighborhood focus using partial disagreements and enhanced exploration capabilities through extreme disagreements.

Keywords

Genetic Algorithm Particle Swarm Optimization Mutation Operator Partial Disagreement Extreme Disagreement 
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 2011

Authors and Affiliations

  • Andrei Lihu
    • 1
  • Ştefan Holban
    • 1
  1. 1.Department of Computer SciencePolitehnica University of TimişoaraTimişoaraRomania

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