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Enhanced Meta-model Based Optimization under Constraints using Parallel Computations

Article dans une revue avec comité de lecture
Author
EL BECHARI, Reda
BRISSET, Stéphane
MIPO, Jean-Claude
218959 Valeo Engine Cooling
ccCLENET, Stephane
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]

URI
http://hdl.handle.net/10985/13417
DOI
10.1109/TMAG.2017.2761997
Date
2017
Journal
IEEE Transactions on Magnetics

Abstract

Meta-models proved to be a very efficient strategy for optimization of expensive black-box models, e.g. Finite Element simulation for electromagnetic devices. It enables to reduce the computational burden for optimization purposes. Kriging is a popular method to build meta-model. Its statistical properties were firstly used in efficient global optimization for unconstrained problems. Afterwards many extensions were introduced in the literature to deal with constrained optimization. This paper presents a comparative study of some infill criteria for constraints handling and a new strategy for parallelization of the expensive computations of models. TEAM workshop problem 22 is taken as an electromagnetic test problem.

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