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

  • Hans-Georg Beyer
  • Alexander Melkozerov
Conference paper

DOI: 10.1007/978-3-540-87700-4_2

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5199)
Cite this paper as:
Beyer HG., Melkozerov A. (2008) σ-Self-Adaptive Weighted Multirecombination Evolution Strategy with Scaled Weights on the Noisy Sphere. In: Rudolph G., Jansen T., Beume N., Lucas S., Poloni C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg

Abstract

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.

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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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