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PurposeThe purpose of this paper is to present a low evaluation budget optimization strategy for expensive simulation models, such as 3D finite element models.Design/methodology/approachA 3D finite element electromagnetic model and a thermal model are developed and coupled in order to simulate the linear induction motor (LIM) to be conceived. Using the 3D finite element coupling model as a simulation model, a multi‐objective optimization with a progressive improvement of a surrogate model is proposed. The proposed surrogate model is progressively improved using an infill set selection strategy which is well‐suited for the parallel evaluation of the 3D finite element coupling model on an eight‐core machine, with a maximum of four models running in parallel.FindingsThe proposed strategy allows for a significant gain of optimization time. The 3D Pareto front composed of the finite element model evaluation results is obtained, which provides the designer with a set of optimal trade‐off solutions for him/her to make the final decision for the engineering design.Originality/valueAn infill set selection strategy is proposed, which allows the parallel evaluation of the finite element model, and at the same time guides the progressive construction of an improved surrogate model during the multi‐objective optimization run. The paper may stand as a good reference for researchers/engineering designers who have to deal with optimal design problems implying costly simulation models.

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Purpose -The purpose of this paper is to present an application of a multidisciplinary multi-level design optimization methodology for the optimal design of a complex device from the field of electrical engineering throughout discipline-based decomposition. The considered benchmark is a single-phase low voltage safety isolation transformer. Design/methodology/approach -The multidisciplinary optimization of a safety isolation transformer is addressed within this paper. The bi-level collaborative optimization (CO) strategy is employed to coordinate the optimization of the different disciplinary analytical models of the transformer (no-load and full-load electromagnetic models and thermal model). The results represent the joint decision of the three distinct disciplinary optimizers involved in the design process, under the coordination of the CO's master optimizer. In order to validate the proposed approach, the results are compared to those obtained using a classical single-level optimization method -sequential quadratic programming -carried out using a multidisciplinary feasible formulation for handling the evaluation of the coupling model of the transformer. Findings -Results show a good convergence of the CO process with the analytical modeling of the transformer, with a reduced number of coordination iterations. However, a relatively important number of disciplinary models evaluations were required by the local optimizers. Originality/value -The CO multi-level methodology represents a new approach in the field of electrical engineering. The advantage of this approach consists in that it integrates decisions from different teams of specialists within the optimal design process of complex systems and all exchanges are managed within a unique coordination process.