Enhanced Meta-model Based Optimization under Constraints using Parallel Computations
Article dans une revue avec comité de lecture
Auteur
EL BECHARI, RedaBRISSET, StéphaneMIPO, Jean-Claude 
CLENET, StephaneRésumé
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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