Many Objective Optimization of a Magnetic Micro–Electro–Mechanical (MEMS) Micromirror with Bounded MP-NSGA Algorithm

Paolo Di Barba, Maria Evelina Mognaschi and Elisabetta Sieni
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Paolo Di Barba: Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, Italy
Maria Evelina Mognaschi: Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, Italy
Elisabetta Sieni: Department of Theoretical and Applied Sciences–DiSTA, University of Insubria, via J.H. Dunant, 3, 21100 Varese, Italy

Mathematics, 2020, vol. 8, issue 9, 1-17

Abstract: The paper proposes the automated optimal design of a class of micro–electro–mechanical (MEMS) devices, based on a procedure of finite element analysis coupled to evolutionary optimization algorithms. A magnetic MEMS, used as an optical switch, is considered as the case study. In particular, the geometry of the device is optimized in order to maximize the actuation torque and minimize the power losses and the device volume. The optimization algorithms belong to the genetic class and, in particular, Migrated Parents - Non-Dominated Sorting Genetic Algorithm MP-NSGA, with three objective functions, is compared to NSGA-III.

Keywords: MEMS; micromirror; magnetic field; finite element analysis; many-objective optimization; Pareto Front (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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