Local Meta-models for Optimization Using Evolution Strategies

  • Stefan Kern
  • Nikolaus Hansen
  • Petros Koumoutsakos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)


We employ local meta-models to enhance the efficiency of evolution strategies in the optimization of computationally expensive problems. The method involves the combination of second order local regression meta-models with the Covariance Matrix Adaptation Evolution Strategy. Experiments on benchmark problems demonstrate that the proposed meta-models have the potential to reliably account for the ranking of the offspring population resulting in significant computational savings. The results show that the use of local meta-models significantly increases the efficiency of already competitive evolution strategies.


Local Model Evaluation Fraction Meta Model Multimodal Function Bandwidth Parameter 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Stefan Kern
    • 1
  • Nikolaus Hansen
    • 1
  • Petros Koumoutsakos
    • 1
  1. 1.Computational Science and Engineering Laboratory, Institute of Computational ScienceETH ZurichSwitzerland

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