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Tipo da ReferênciaJournal Article
Identificador8JMKD3MGP3W34P/3LKHL9E
Repositóriosid.inpe.br/mtc-m21b/2016/05.03.12.38   (acesso restrito)
Metadadossid.inpe.br/mtc-m21b/2016/05.03.12.38.49
Sitemtc-m21b.sid.inpe.br
DOI10.1364/OE.24.006619
ISSN1094-4087
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Chave de CitaçãoAlbuquerqueSousMont:2016:MuApAu
Autor1 Albuquerque, Bráulio Fonseca Carneiro de
2 Sousa, Fabiano Luis de
3 Montes, Amauri Silva
Identificador de Curriculo1 8JMKD3MGP5W/3C9JGKR
2 8JMKD3MGP5W/3C9JH3H
3 8JMKD3MGP5W/3C9JGH5
Grupo1 DEA-ETE-INPE-MCTI-GOV-BR
2 DSE-ETE-INPE-MCTI-GOV-BR
3 ETE-ETE-INPE-MCTI-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 brauliofca@gmail.com
2 fabiano.sousa@inpe.br
3 amauri.montes@inpe.br
TítuloMulti-objective approach for the automatic design of optical systems
RevistaOptics Express
Ano2016
Volume24
Número6
MêsMar.
Palavras-Chavelgorithms, Design, Economic and social effects, Efficiency, Least squares approximations, Lenses, Multiobjective optimization, Optical glass, Optical instrument lenses, Optical systems, Optimization, Orbits.
ResumoAn innovative method for the automatic design of optical systems is presented and verified. The proposed method is based on a multiobjective evolutionary memetic optimization algorithm. The multi-objective approach simultaneously, but separately, addresses the image quality, tolerance, and complexity of the system. The memetic technique breaks down the search for optical designs in to three different parts or phases: optical glass selection, exploration, and exploitation. The optical glass selection phase defines the most appropriate set of glasses for the system under design. The glass selection phase limits the available glasses from hundreds to just a few, drastically reducing the design space and significantly increasing the efficiency of the automatic design method. The exploration phase is based on an evolutionary algorithm (EA), more specifically, on a problem-tailored generalized extremal optimization (GEO) algorithm, named Optical GEO (O-GEO). The new EA incorporates many features customized for lens design, such as optical system codification and diversity operators. The trade-off systems found in the exploration phase are refined by a local search, based on the damped least square method in the exploitation phase. As a result, the method returns a set of trade-off solutions, generating a Pareto front. Our method delivers alternative and useful insights for the compromise solutions in a lens design problem. The efficiency of the proposed method is verified through realworld examples, showing excellent results for the tested problems.
Páginas6619-6643
Idiomaen
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
DivulgaçãoWEBSCI; PORTALCAPES; COMPENDEX; SCOPUS.
AreaETES
Nota SecundáriaA1_ODONTOLOGIA A1_INTERDISCIPLINAR A1_ENGENHARIAS_IV A1_ENGENHARIAS_III A2_QUÍMICA A2_MEDICINA_III A2_MEDICINA_II A2_MATERIAIS A2_ENGENHARIAS_II A2_BIOTECNOLOGIA A2_ASTRONOMIA_/_FÍSICA B1_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA B1_CIÊNCIA_DA_COMPUTAÇÃO
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