A multi-objective evolutionary algorithm based on decomposition for optimal design of Yagi-Uda antennas.

dc.contributor.authorCarvalho, Rodrigo de
dc.contributor.authorSaldanha, Rodney Rezende
dc.contributor.authorGomes, B. N.
dc.contributor.authorLisboa, Adriano Chaves
dc.contributor.authorAlexandre, Xavier Martins
dc.date.accessioned2012-10-09T17:36:28Z
dc.date.available2012-10-09T17:36:28Z
dc.date.issued2012
dc.description.abstractThis paper presents a multi-objective evol utionary algorithm based on decomposition (MOEA/D) to design broadband optimal Yagi-Uda antennas. A multi-objective problem is formulated to achieve maximum directivity, minimum voltage standing wave ratio and maximum front-to-back ratio. The algorithm was applied to th e design of optimal 3 to 10 elements Yagi-Uda antennas, whose optimal Pareto fronts are provided in a single picture. The multi-o bjective problem is decomposed by Chebyshev decomposition, and it is solved by differential evolution (DE) and Gaussian mutation op erators in order to provide a better approximation of the Pareto front. The results show that the implemented MOEA/D is ef fi cient for designing Yagi-Uda antennas.pt_BR
dc.identifier.citationCARVALHO, R. de et al. A multi-objective evolutionary algorithm based on decomposition for optimal design of Yagi-Uda antennas. IEEE Transactions on Magnetic, v. 48, n.2, p. 803-806, 2012. Disponível em: <http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6136618>. Acesso em: 10 out. 2012.pt_BR
dc.identifier.issn00189464
dc.identifier.urihttp://www.repositorio.ufop.br/handle/123456789/1585
dc.identifier.uri2http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6136618
dc.language.isoen_USpt_BR
dc.subjectMulti-objective optimizationpt_BR
dc.subjectDecomposition problempt_BR
dc.subjectDesigning Yagi-U da antennapt_BR
dc.titleA multi-objective evolutionary algorithm based on decomposition for optimal design of Yagi-Uda antennas.pt_BR
dc.typeArtigo publicado em periodicopt_BR
Arquivos
Pacote Original
Agora exibindo 1 - 1 de 1
Nenhuma Miniatura disponível
Nome:
ARTIGO_MultiObjectiveEvolutionary.pdf
Tamanho:
617.51 KB
Formato:
Adobe Portable Document Format
Licença do Pacote
Agora exibindo 1 - 1 de 1
Nenhuma Miniatura disponível
Nome:
license.txt
Tamanho:
1.71 KB
Formato:
Item-specific license agreed upon to submission
Descrição: