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HPC Implementation of the Multipoint Approximation Method for Large Scale Design Optimization Problems Under Uncertainty

  • Vassili ToropovEmail author
  • Yury Korolev
  • Konstantin Barkalov
  • Evgeny Kozinov
  • Victor Gergel
Conference paper

Abstract

The paper presents an HPC implementation of the Multipoint Approximation Method (MAM) applied to problems with uncertainty in design variables as well as in additional environmental variables. The approach relies on approximations built in the combined space of design variables and environmental variables, and subsequent application of a risk measure and optimization with respect to the deterministic design variables, all within the iterative trust-region-based framework of MAM.

Keywords

Design optimization Uncertainty Multipoint Approximation Method HPC 

Notes

Acknowledgment

Vassili Toropov, Konstantin Barkalov, Evgeny Kozinov and Victor Gergel are grateful for the support provided by the Russian Science Foundation, Project No. 16-11-10150.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Queen Mary University of LondonLondonUK
  2. 2.Lobachevsky State University of Nizhny NovgorodNizhny NovgorodRussia
  3. 3.Cambridge UniversityCambridgeUK

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