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On the Asymptotic Tractability of Global Optimization

  • James M. CalvinEmail author
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 107)

Abstract

We consider the intrinsic difficulty of global optimization in high dimensional Euclidean space. We adopt an asymptotic analysis, and give a lower bound on the number of function evaluations required to obtain a given error tolerance. This lower bound complements upper bounds provided by recently proposed algorithms.

Keywords

Lower complexity bounds Tractability Adaptive algorithms 

Notes

Acknowledgements

The motivation for this investigation grew out of discussions with A. Žilinskas.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.New Jersey Institute of TechnologyNewarkUSA

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