Enhanced Meta-Model-Based Optimization Under Constraints Using Parallel Computations
Reda El Bechari, Stéphane Brisset, Stephane Clenet, J. C. Mipo · IEEE Transactions on Magnetics · 2017
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 first used in efficient global optimization for unconstrained problems. Afterward, 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.