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Metadados

1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m16.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador6qtX3pFwXQZsFDuKxG/DbM9M
Repositóriosid.inpe.br/marciana/2004/08.17.15.27   (acesso restrito)
Última Atualização2004:08.17.03.00.00 (UTC) administrator
Repositório de Metadadossid.inpe.br/marciana/2004/08.17.15.27.49
Última Atualização dos Metadados2018:06.05.01.28.42 (UTC) administrator
Chave SecundáriaINPE-11221-PRE/6670
ISBN/ISSN0377-2217
ISSN0377-2217
Chave de CitaçãoNarcisoLore:1999:LaReGe
TítuloLagrangean/surrogate relaxation for generalized assignment problems
Ano1999
MêsApr.
Data de Acesso22 maio 2024
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho158 KiB
2. Contextualização
Autor1 Narciso, M. G.
2 Lorena, Luiz Antonio Nogueira
Identificador de Curriculo1
2 8JMKD3MGP5W/3C9JHMQ
Grupo1 LAC-INPE-MCT-BR
RevistaEuropean Journal of Operational Research
Volume114
Número1
Páginas165-177
Histórico (UTC)2006-09-28 22:36:24 :: administrator -> sergio ::
2008-01-07 12:49:58 :: sergio -> administrator ::
2018-06-05 01:28:42 :: administrator -> marciana :: 1999
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Palavras-Chaverelaxation
Lagrangean and surrogate relaxation
generalized assignment problem / SUBGRADIENT METHOD
KNAPSACK-PROBLEM
SHORTEST-PATH
ALGORITHM
OPTIMIZATION
CONSTRAINTS
MODEL
ResumoThis work presents Lagrangean/surrogate relaxation to the problem of maximum profit assignment of n tasks to m agents (n > m), such that each task is assigned to only one agent subject to capacity constraints on the agents. The Lagrangean/surrogate relaxation combines usual Lagrangean and surrogate relaxations relaxing first a set of constraints in the surrogate way. Then, the Lagrangean relaxation of the surrogate constraint is obtained and approximately optimized (one-dimensional dual). The Lagrangean/surrogate is compared with the usual Lagrangean relaxation on a computational study using a large set of instances. The dual bounds are the same for both relaxations, but the Lagrangean/surrogate can give improved local bounds at the application of a subgradient method, resulting in less computational times. Three relaxations are derived for the problem. The first relaxation considers a vector of multipliers for the capacity constraints, the second for the assignment constraints and the other for the Lagrangean decomposition constraints. Relaxation multipliers are used with efficient constructive heuristics to find good feasible solutions. The application of a Lagrangean/surrogate approach seems very promising for large scale problems. (C) 1999 Elsevier Science B.V. All rights reserved.
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4. Condições de acesso e uso
Idiomaen
Arquivo Alvolagrangean.pdf
Grupo de Usuáriosadministrator
sergio
Visibilidadeshown
Detentor da CópiaSID/SCD
Política de Arquivamentodenypublisher denyfinaldraft36
Permissão de Leituradeny from all and allow from 150.163
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/3ESGTTP
DivulgaçãoWEBSCI; PORTALCAPES.
Acervo Hospedeirosid.inpe.br/banon/2003/08.15.17.40
6. Notas
Campos Vaziosaffiliation alternatejournal archivist callnumber copyright creatorhistory descriptionlevel documentstage doi e-mailaddress electronicmailaddress format isbn label lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url versiontype
7. Controle da descrição
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