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Iterative Kriging-based Methods for Expensive Black-Box Models

Article dans une revue avec comité de lecture
Author
DENG, Siyang
EL BECHARI, Reda
BRISSET, Stéphane
ccCLENET, Stephane
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]

URI
http://hdl.handle.net/10985/12996
DOI
10.1109/TMAG.2017.2767706
Date
2018
Journal
IEEE Transactions on Magnetics

Abstract

Reliability-Based Design Optimization (RBDO) in electromagnetic field problems requires the calculation of probability of failure leading to a huge computational cost in the case of expensive models. Three different RBDO approaches using kriging surrogate model are proposed to overcome this difficulty by introducing an approximation of the objective function and constraints. These methods use different infill sampling criteria (ISC) to add samples in the process of optimization or/and in the reliability analysis. Several enrichment criteria and strategies are compared in terms of number of evaluations and accuracy of the solution.

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