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

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 geom...

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Bibliographic Details
Published in:Mathematics (Basel) 2020-09, Vol.8 (9), p.1509
Main Authors: Di Barba, Paolo, Mognaschi, Maria, Sieni, Elisabetta
Format: Article
Language:English
Subjects:
Actuation
Algorithms
Design
Embedded systems
Evolutionary algorithms
finite element analysis
Finite element method
Genetic algorithms
Inverse problems
magnetic field
Magnetic fields
many-objective optimization
Mathematical problems
Mathematics
MEMS
Microelectromechanical systems
micromirror
Optical switching
Optimization
Pareto Front
Permeability
Sensors
Sorting algorithms
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Summary: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.
ISSN:2227-7390
2227-7390
DOI:10.3390/math8091509