Branch and Bound Algorithm Based on Prediction Error of Metamodel for Computational Electromagnetics

Reda El Bechari, Stéphane Brisset, Stéphane Clénet, Frédéric Guyomarch and Jean Claude Mipo
Additional contact information
Reda El Bechari: University Lille, Arts et Metiers Institute of Technology, Centrale Lille, Junia, ULR 2697-L2EP, F-59000 Lille, France
Stéphane Brisset: University Lille, Arts et Metiers Institute of Technology, Centrale Lille, Junia, ULR 2697-L2EP, F-59000 Lille, France
Stéphane Clénet: University Lille, Arts et Metiers Institute of Technology, Centrale Lille, Junia, ULR 2697-L2EP, F-59000 Lille, France
Frédéric Guyomarch: University Lille, Arts et Metiers Institute of Technology, Centrale Lille, Junia, ULR 2697-L2EP, F-59000 Lille, France
Jean Claude Mipo: Valeo Powertrain Systems, F-94000 Créteil, France

Energies, 2020, vol. 13, issue 24, 1-16

Abstract: Metamodels proved to be a very efficient strategy for optimizing expensive black-box models, e.g., Finite Element simulation for electromagnetic devices. It enables the reduction of the computational burden for optimization purposes. However, the conventional approach of using metamodels presents limitations such as the cost of metamodel fitting and infill criteria problem-solving. This paper proposes a new algorithm that combines metamodels with a branch and bound (B&B) strategy. However, the efficiency of the B&B algorithm relies on the estimation of the bounds; therefore, we investigated the prediction error given by metamodels to predict the bounds. This combination leads to high fidelity global solutions. We propose a comparison protocol to assess the approach’s performances with respect to those of other algorithms of different categories. Then, two electromagnetic optimization benchmarks are treated. This paper gives practical insights into algorithms that can be used when optimizing electromagnetic devices.

Keywords: electromagnetic; finite element method; metamodel; optimization methods; TEAM Workshop problems (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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