Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problems

Detalhes bibliográficos
Autor(a) principal: Ciappina, Jussara Rodrigues
Data de Publicação: 2012
Outros Autores: Yamakami, Akebo, Silva, Ricardo Coelho [UNIFESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNIFESP
Texto Completo: http://dx.doi.org/10.1016/j.cor.2012.04.023
http://repositorio.unifesp.br/handle/11600/35518
Resumo: We present, in this paper, a method for solving linear programming problems with fuzzy costs based on the classical method of decomposition's Dantzig-Wolfe. Methods using decomposition techniques address problems that have a special structure in the set of constraints. An example of such a problem that has this structure is the fuzzy multicommodity flow problem. This problem can be modeled by a graph whose nodes represent points of supply, demand and passage of commodities, which travel on the arcs of the network. the objective is to determine the flow of each commodity on the arcs, in order to meet demand at minimal cost while respecting the capacity constraints of the arcs and the flow conservation constraints of the nodes. Using the theory of fuzzy sets, the proposed method aims to find the optimal solution, working with the problem in the fuzzy form during the resolution procedure. (c) 2012 Elsevier B.V. All rights reserved.
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spelling Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problemsFuzzy linear programmingDecompositionFuzzy multicommodity flowWe present, in this paper, a method for solving linear programming problems with fuzzy costs based on the classical method of decomposition's Dantzig-Wolfe. Methods using decomposition techniques address problems that have a special structure in the set of constraints. An example of such a problem that has this structure is the fuzzy multicommodity flow problem. This problem can be modeled by a graph whose nodes represent points of supply, demand and passage of commodities, which travel on the arcs of the network. the objective is to determine the flow of each commodity on the arcs, in order to meet demand at minimal cost while respecting the capacity constraints of the arcs and the flow conservation constraints of the nodes. Using the theory of fuzzy sets, the proposed method aims to find the optimal solution, working with the problem in the fuzzy form during the resolution procedure. (c) 2012 Elsevier B.V. All rights reserved.Univ Campinas UNICAMP, Sch Elect & Comp Engn, BR-13083852 Campinas, SP, BrazilUNIFESP, ICT, BR-12231280 Sao Jose Dos Campos, SP, BrazilUNIFESP, ICT, BR-12231280 Sao Jose Dos Campos, SP, BrazilWeb of ScienceCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Elsevier B.V.Universidade Estadual de Campinas (UNICAMP)Universidade Federal de São Paulo (UNIFESP)Ciappina, Jussara RodriguesYamakami, AkeboSilva, Ricardo Coelho [UNIFESP]2016-01-24T14:28:02Z2016-01-24T14:28:02Z2012-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion3394-3407application/pdfhttp://dx.doi.org/10.1016/j.cor.2012.04.023Computers & Operations Research. Oxford: Pergamon-Elsevier B.V., v. 39, n. 12, p. 3394-3407, 2012.10.1016/j.cor.2012.04.023WOS000313379300041.pdf0305-0548http://repositorio.unifesp.br/handle/11600/35518WOS:000313379300041engComputers & Operations Researchinfo:eu-repo/semantics/openAccesshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policyreponame:Repositório Institucional da UNIFESPinstname:Universidade Federal de São Paulo (UNIFESP)instacron:UNIFESP2024-08-01T03:26:58Zoai:repositorio.unifesp.br/:11600/35518Repositório InstitucionalPUBhttp://www.repositorio.unifesp.br/oai/requestbiblioteca.csp@unifesp.bropendoar:34652024-08-01T03:26:58Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)false
dc.title.none.fl_str_mv Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problems
title Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problems
spellingShingle Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problems
Ciappina, Jussara Rodrigues
Fuzzy linear programming
Decomposition
Fuzzy multicommodity flow
title_short Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problems
title_full Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problems
title_fullStr Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problems
title_full_unstemmed Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problems
title_sort Decomposition's Dantzig-Wolfe applied to fuzzy multicommodity flow problems
author Ciappina, Jussara Rodrigues
author_facet Ciappina, Jussara Rodrigues
Yamakami, Akebo
Silva, Ricardo Coelho [UNIFESP]
author_role author
author2 Yamakami, Akebo
Silva, Ricardo Coelho [UNIFESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual de Campinas (UNICAMP)
Universidade Federal de São Paulo (UNIFESP)
dc.contributor.author.fl_str_mv Ciappina, Jussara Rodrigues
Yamakami, Akebo
Silva, Ricardo Coelho [UNIFESP]
dc.subject.por.fl_str_mv Fuzzy linear programming
Decomposition
Fuzzy multicommodity flow
topic Fuzzy linear programming
Decomposition
Fuzzy multicommodity flow
description We present, in this paper, a method for solving linear programming problems with fuzzy costs based on the classical method of decomposition's Dantzig-Wolfe. Methods using decomposition techniques address problems that have a special structure in the set of constraints. An example of such a problem that has this structure is the fuzzy multicommodity flow problem. This problem can be modeled by a graph whose nodes represent points of supply, demand and passage of commodities, which travel on the arcs of the network. the objective is to determine the flow of each commodity on the arcs, in order to meet demand at minimal cost while respecting the capacity constraints of the arcs and the flow conservation constraints of the nodes. Using the theory of fuzzy sets, the proposed method aims to find the optimal solution, working with the problem in the fuzzy form during the resolution procedure. (c) 2012 Elsevier B.V. All rights reserved.
publishDate 2012
dc.date.none.fl_str_mv 2012-12-01
2016-01-24T14:28:02Z
2016-01-24T14:28:02Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.cor.2012.04.023
Computers & Operations Research. Oxford: Pergamon-Elsevier B.V., v. 39, n. 12, p. 3394-3407, 2012.
10.1016/j.cor.2012.04.023
WOS000313379300041.pdf
0305-0548
http://repositorio.unifesp.br/handle/11600/35518
WOS:000313379300041
url http://dx.doi.org/10.1016/j.cor.2012.04.023
http://repositorio.unifesp.br/handle/11600/35518
identifier_str_mv Computers & Operations Research. Oxford: Pergamon-Elsevier B.V., v. 39, n. 12, p. 3394-3407, 2012.
10.1016/j.cor.2012.04.023
WOS000313379300041.pdf
0305-0548
WOS:000313379300041
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Computers & Operations Research
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
http://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
eu_rights_str_mv openAccess
rights_invalid_str_mv http://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.format.none.fl_str_mv 3394-3407
application/pdf
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv reponame:Repositório Institucional da UNIFESP
instname:Universidade Federal de São Paulo (UNIFESP)
instacron:UNIFESP
instname_str Universidade Federal de São Paulo (UNIFESP)
instacron_str UNIFESP
institution UNIFESP
reponame_str Repositório Institucional da UNIFESP
collection Repositório Institucional da UNIFESP
repository.name.fl_str_mv Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)
repository.mail.fl_str_mv biblioteca.csp@unifesp.br
_version_ 1814268403466108928

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