Biogeography-Inspired Multiobjective Optimization and MEMS Design

A new version of the biogeography-based optimization algorithm is proposed in order to consider multiple objectives. In fact, by exploiting non-dominated sorting of habitats, it is possible to approximate Pareto-optimal solutions in the objective space. The optimal shape design of an electrostatic m...

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Bibliographic Details
Published inIEEE transactions on magnetics Vol. 52; no. 3; pp. 1 - 4
Main Authors Di Barba, P., Dughiero, F., Mognaschi, M. E., Savini, A., Wiak, S.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.03.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithm design and analysis
Algorithms
Approximation
Benchmarking
Biogeography-inspired optimization
Design engineering
Design optimization
electrostatic field
Electrostatics
Indexes
Linear programming
Magnetism
MEMS
Micromotors
Optimization
Pareto optimality
Rotors
Systems design
Pareto optimality
Biogeography-inspired optimization
micro electro-mechanical systems (MEMS)
electrostatic field
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Summary:A new version of the biogeography-based optimization algorithm is proposed in order to consider multiple objectives. In fact, by exploiting non-dominated sorting of habitats, it is possible to approximate Pareto-optimal solutions in the objective space. The optimal shape design of an electrostatic micromotor, which is a benchmark in the Micro Electro-Mechanical Systems design, is considered as the case study.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2015.2488982