Safety Isolating Transformer Design using HyDE-DF algorithm

Abstract

This paper presents an application of Evolutionary Computation (EC) to the benchmark of the safety isolating transformer problem. The benchmark adopts multidisciplinary optimization strategies, namely the multidisciplinary feasible (MDF) and the individual discipline feasible (IDF) formulations. The benchmark meets the requirements of engineers and scientists working with machine design problem, such as in the first part of the design process that is the choice of structure and materials. The EC methods employed in this paper are based on Evolutionary Algorithms (EAs), namely two variants of Differential Evolution (DE), two variants of Hybrid Adaptive DE (HyDE) and the Vortex Search (VS). The results showed in this paper suggest that EA methods are competitive with the classical optimization method, the sequential quadratic programming (SQP). Among the developed EAs, HyDE-DF is able to obtain better values than SQP on a significant battery of trials.This research has received funding from FEDER funds through the Op-erational Programme for Competitiveness and Internationalization (COM-PETE 2020), under Project POCI-01-0145-FEDER-028983;by NationalFunds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017 (CENERGETIC), and UIDB/00760/2020; Joao Soares is supported by FCT CEECIND/02814/2017grant.info:eu-repo/semantics/publishedVersio