Enhanced Meta-model Based Optimization under Constraints using Parallel Computations - Archive ouverte HAL
Article Dans Une Revue IEEE Transactions on Magnetics Année : 2017

Enhanced Meta-model Based Optimization under Constraints using Parallel Computations

Résumé

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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Dates et versions

hal-01858636 , version 1 (21-08-2018)

Identifiants

Citer

Reda El Bechari, Stephane Brisset, Stephane Clenet, Jean Claude Mipo. Enhanced Meta-model Based Optimization under Constraints using Parallel Computations. IEEE Transactions on Magnetics, 2017, 54 (3), pp.1-4. ⟨10.1109/TMAG.2017.2761997⟩. ⟨hal-01858636⟩
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