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

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...

Full description

Bibliographic Details
Main Authors: Paolo Di Barba, Maria Evelina Mognaschi, Elisabetta Sieni
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Mathematics
Subjects:
MEMS
micromirror
magnetic field
finite element analysis
many-objective optimization
Pareto Front
Online Access:https://www.mdpi.com/2227-7390/8/9/1509
id doaj-dc59dbd8662e474cae31c02499961af6
record_format Article
spelling doaj-dc59dbd8662e474cae31c02499961af62020-11-25T02:44:17ZengMDPI AGMathematics2227-73902020-09-0181509150910.3390/math8091509Many Objective Optimization of a Magnetic Micro–Electro–Mechanical (MEMS) Micromirror with Bounded MP-NSGA AlgorithmPaolo Di Barba0Maria Evelina Mognaschi1Elisabetta Sieni2Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, ItalyDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, ItalyDepartment of Theoretical and Applied Sciences–DiSTA., University of Insubria, via J.H. Dunant, 3., 21100 Varese, ItalyThe 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.https://www.mdpi.com/2227-7390/8/9/1509MEMSmicromirrormagnetic fieldfinite element analysismany-objective optimizationPareto Front
collection DOAJ
language English
format Article
sources DOAJ
author Paolo Di Barba
Maria Evelina Mognaschi
Elisabetta Sieni
spellingShingle Paolo Di Barba
Maria Evelina Mognaschi
Elisabetta Sieni
Many Objective Optimization of a Magnetic Micro–Electro–Mechanical (MEMS) Micromirror with Bounded MP-NSGA Algorithm
Mathematics
MEMS
micromirror
magnetic field
finite element analysis
many-objective optimization
Pareto Front
author_facet Paolo Di Barba
Maria Evelina Mognaschi
Elisabetta Sieni
author_sort Paolo Di Barba
title Many Objective Optimization of a Magnetic Micro–Electro–Mechanical (MEMS) Micromirror with Bounded MP-NSGA Algorithm
title_short Many Objective Optimization of a Magnetic Micro–Electro–Mechanical (MEMS) Micromirror with Bounded MP-NSGA Algorithm
title_full Many Objective Optimization of a Magnetic Micro–Electro–Mechanical (MEMS) Micromirror with Bounded MP-NSGA Algorithm
title_fullStr Many Objective Optimization of a Magnetic Micro–Electro–Mechanical (MEMS) Micromirror with Bounded MP-NSGA Algorithm
title_full_unstemmed Many Objective Optimization of a Magnetic Micro–Electro–Mechanical (MEMS) Micromirror with Bounded MP-NSGA Algorithm
title_sort many objective optimization of a magnetic micro–electro–mechanical (mems) micromirror with bounded mp-nsga algorithm
publisher MDPI AG
series Mathematics
issn 2227-7390
publishDate 2020-09-01
description 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.
topic MEMS
micromirror
magnetic field
finite element analysis
many-objective optimization
Pareto Front
url https://www.mdpi.com/2227-7390/8/9/1509
work_keys_str_mv AT paolodibarba manyobjectiveoptimizationofamagneticmicroelectromechanicalmemsmicromirrorwithboundedmpnsgaalgorithm
AT mariaevelinamognaschi manyobjectiveoptimizationofamagneticmicroelectromechanicalmemsmicromirrorwithboundedmpnsgaalgorithm
AT elisabettasieni manyobjectiveoptimizationofamagneticmicroelectromechanicalmemsmicromirrorwithboundedmpnsgaalgorithm
_version_ 1724766631238828032

Similar Items