Research on Convergence of Self-adaptive Mutation Algorithm

  • Li Huang
  • Weiwei Du
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 124)

Abstract

We proposed a self-adaptive mutation algorithm which is varying mutation probability with evolutionary generation. Then, certify the convergence of this algorithm with the matrix theory and Markov chain and obtain the idea that this adaptive algorithm converges to the optimum with the probability.

Keywords

Markov Chain Markov Chain Theory Absorb Markov Chain Random Variable Sequence Inhomogeneous Markov Chain 
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

  • Li Huang
    • 1
  • Weiwei Du
    • 2
  1. 1.Department of MathematicsWuhan University of TechnologyWuhanChina
  2. 2.North Automatic Control Technology InstituteTaiyunChina

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