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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
24/01/1994 |
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Data da última atualização: |
08/10/2022 |
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Tipo da produção científica: |
Folder/Folheto/Cartilha |
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Autoria: |
FARIA, M. E. de; TEIXEIRA, S. M.; DEL PELOSO, M. J.; SILVA, I. M. da. |
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Afiliação: |
MAGDA EVA DE FARIA, EMGOPA; SONIA MILAGRES TEIXEIRA, CNPAF; MARIA JOSE DEL PELOSO, CNPAF; INALDIZA MEDEIROS DA SILVA, estagiária CNPAF. |
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Título: |
Feijão irrigado: fortalecimento da agricultura empresarial. |
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Ano de publicação: |
1992 |
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Fonte/Imprenta: |
Goiânia: EMGOPA, 1992. |
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Páginas: |
56 p. |
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Série: |
(EMGOPA. Documentos, 21). |
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ISSN: |
0102-7042 |
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Idioma: |
Português |
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Thesagro: |
Economia; Feijão; Phaseolus Vulgaris. |
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Categoria do assunto: |
E Economia e Indústria Agrícola |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/194179/1/Documentos-21.pdf
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Marc: |
LEADER 00542nam a2200205 a 4500
001 1194179
005 2022-10-08
008 1992 bl uuuu 00u1 u #d
022 $a0102-7042
100 1 $aFARIA, M. E. de
245 $aFeijão irrigado$bfortalecimento da agricultura empresarial.
260 $aGoiânia: EMGOPA$c1992
300 $a56 p.
490 $a(EMGOPA. Documentos, 21).
650 $aEconomia
650 $aFeijão
650 $aPhaseolus Vulgaris
700 1 $aTEIXEIRA, S. M.
700 1 $aDEL PELOSO, M. J.
700 1 $aSILVA, I. M. da
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Unidades Centrais. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
25/09/1997 |
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Data da última atualização: |
31/08/2007 |
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Autoria: |
PEDROSO, M. |
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Afiliação: |
CNPTIA. |
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Título: |
Hybrid ellipsoid-sequential quadratic programming algorithms. |
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Ano de publicação: |
1985 |
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Fonte/Imprenta: |
1985. |
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Páginas: |
230p. |
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Idioma: |
Inglês |
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Notas: |
Tese (Doutorado) - Rensselaer, New York Rensselaer Polytechnic Institute. |
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Conteúdo: |
This thesis presents hybrid algorithms for solving constrained nonlinear programming problems. These hybrid methods are obtained by combining variants of the ellipsoid algorithm with variants of the sequential quadratic programming method. The first hybrid method is a two-phases method. In the first phase, the ellipsoid algorithm is used until the active set of problem has been identified. In the second phase, a version of the sequential quadratic programming method is used. The active set identification procedure is based on the frequency of the constraint usage during the iterations of the ellipsoid algorithm. The second hybrid method is a version of the sequential quadratic programming method that invokes the ellipsoid algorithm when the iterations cannotbe completed. Both versions are evaluated by solving a set of 20 widely known test problems, and they prove to perform well. There is also a computational comparison of two efficiente subroutines for solving quadratic programming problems and four implementations of the sequential quadratic programming method. The results obtained indicate that even the simplest implementation of the sequential quadratic programming method with no line search perform competitively with much more sophisticated implementations. |
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Palavras-Chave: |
Algoritmo; Computer; Estatística matemática; Mathematical statistics; Nonlinear programming; Programação; Programação não linear; Programming. |
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Thesagro: |
Computador. |
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Thesaurus NAL: |
algorithms. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01993nam a2200253 a 4500
001 1091395
005 2007-08-31
008 1985 bl uuuu m 00u1 u #d
100 1 $aPEDROSO, M.
245 $aHybrid ellipsoid-sequential quadratic programming algorithms.
260 $a1985.$c1985
300 $a230p.
500 $aTese (Doutorado) - Rensselaer, New York Rensselaer Polytechnic Institute.
520 $aThis thesis presents hybrid algorithms for solving constrained nonlinear programming problems. These hybrid methods are obtained by combining variants of the ellipsoid algorithm with variants of the sequential quadratic programming method. The first hybrid method is a two-phases method. In the first phase, the ellipsoid algorithm is used until the active set of problem has been identified. In the second phase, a version of the sequential quadratic programming method is used. The active set identification procedure is based on the frequency of the constraint usage during the iterations of the ellipsoid algorithm. The second hybrid method is a version of the sequential quadratic programming method that invokes the ellipsoid algorithm when the iterations cannotbe completed. Both versions are evaluated by solving a set of 20 widely known test problems, and they prove to perform well. There is also a computational comparison of two efficiente subroutines for solving quadratic programming problems and four implementations of the sequential quadratic programming method. The results obtained indicate that even the simplest implementation of the sequential quadratic programming method with no line search perform competitively with much more sophisticated implementations.
650 $aalgorithms
650 $aComputador
653 $aAlgoritmo
653 $aComputer
653 $aEstatística matemática
653 $aMathematical statistics
653 $aNonlinear programming
653 $aProgramação
653 $aProgramação não linear
653 $aProgramming
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