σ-Self-Adaptive Weighted Multirecombination Evolution Strategy with Scaled Weights on the Noisy Sphere

  • Hans-Georg Beyer
  • Alexander Melkozerov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5199)


This paper presents a performance analysis of the recently proposed σ-self-adaptive weighted recombination evolution strategy (ES) with scaled weights. The steady state behavior of this ES is investigated for the non-noisy and noisy case, and formulas for the optimal choice of the learning parameter are derived allowing the strategy to reach maximal performance. A comparison between weighted multirecombination ES with σ-self-adaptation (σSA) and with cumulative step size adaptation (CSA) shows that the self-adaptive ES is able to reach similar (or even better) performance as its CSA counterpart on the noisy sphere.


Evolution Strategy Progress Rate Steady State Behavior Noise Strength Covariance Matrix Adaptation 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Hans-Georg Beyer
    • 1
  • Alexander Melkozerov
    • 1
  1. 1.Research Center Process and Product Engineering, Department of Computer ScienceVorarlberg University of Applied SciencesDornbirnAustria

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