Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments

Autores
Zamarripa, Miguel A.; Aguirre, Adrian Marcelo; Mendez, Carlos Alberto; Espuña, Antonio
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This work proposes to improve the tactical decision-making of a supply chain (SC) under an uncertain competition scenario through the use of different optimization criteria, which allows to manage not only the specific objectives of the SC of interest, but also the way how its clients address their selection between different potential suppliers, identifying best market share for the SC of interest and the strategy to attain it. The resulting multi-objective optimization problem has been solved using the ɛ-constraint method in order to approximate the Pareto space of non-dominated solutions while a framework based on game theory is used as a reactive decision making support tool to deal with the uncertainty of the competitive scenario. The use of the proposed system is illustrated through its application to a multi-product, multi-echelon supply chain case study, which is intended to cooperate or to compete with another SC of similar characteristics.
Fil: Zamarripa, Miguel A.. Universidad Politecnica de Catalunya; España
Fil: Aguirre, Adrian Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Espuña, Antonio. Universidad Politecnica de Catalunya; España
Materia
Supply Chain Management
Multi-Objective Optimization
Game Theory
Competitive Scenarios
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/8570
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environmentsZamarripa, Miguel A.Aguirre, Adrian MarceloMendez, Carlos AlbertoEspuña, AntonioSupply Chain ManagementMulti-Objective OptimizationGame TheoryCompetitive Scenarioshttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2This work proposes to improve the tactical decision-making of a supply chain (SC) under an uncertain competition scenario through the use of different optimization criteria, which allows to manage not only the specific objectives of the SC of interest, but also the way how its clients address their selection between different potential suppliers, identifying best market share for the SC of interest and the strategy to attain it. The resulting multi-objective optimization problem has been solved using the ɛ-constraint method in order to approximate the Pareto space of non-dominated solutions while a framework based on game theory is used as a reactive decision making support tool to deal with the uncertainty of the competitive scenario. The use of the proposed system is illustrated through its application to a multi-product, multi-echelon supply chain case study, which is intended to cooperate or to compete with another SC of similar characteristics.Fil: Zamarripa, Miguel A.. Universidad Politecnica de Catalunya; EspañaFil: Aguirre, Adrian Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Espuña, Antonio. Universidad Politecnica de Catalunya; EspañaInst Chemical Engineers2013-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/8570Zamarripa, Miguel A.; Aguirre, Adrian Marcelo; Mendez, Carlos Alberto; Espuña, Antonio; Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments; Inst Chemical Engineers; Chemical Engineering Research & Design; 91; 8; 6-2013; 1588-16000263-8762enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.cherd.2013.06.008info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0263876213002517info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:43:49Zoai:ri.conicet.gov.ar:11336/8570instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:43:49.976CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments
title Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments
spellingShingle Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments
Zamarripa, Miguel A.
Supply Chain Management
Multi-Objective Optimization
Game Theory
Competitive Scenarios
title_short Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments
title_full Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments
title_fullStr Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments
title_full_unstemmed Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments
title_sort Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments
dc.creator.none.fl_str_mv Zamarripa, Miguel A.
Aguirre, Adrian Marcelo
Mendez, Carlos Alberto
Espuña, Antonio
author Zamarripa, Miguel A.
author_facet Zamarripa, Miguel A.
Aguirre, Adrian Marcelo
Mendez, Carlos Alberto
Espuña, Antonio
author_role author
author2 Aguirre, Adrian Marcelo
Mendez, Carlos Alberto
Espuña, Antonio
author2_role author
author
author
dc.subject.none.fl_str_mv Supply Chain Management
Multi-Objective Optimization
Game Theory
Competitive Scenarios
topic Supply Chain Management
Multi-Objective Optimization
Game Theory
Competitive Scenarios
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This work proposes to improve the tactical decision-making of a supply chain (SC) under an uncertain competition scenario through the use of different optimization criteria, which allows to manage not only the specific objectives of the SC of interest, but also the way how its clients address their selection between different potential suppliers, identifying best market share for the SC of interest and the strategy to attain it. The resulting multi-objective optimization problem has been solved using the ɛ-constraint method in order to approximate the Pareto space of non-dominated solutions while a framework based on game theory is used as a reactive decision making support tool to deal with the uncertainty of the competitive scenario. The use of the proposed system is illustrated through its application to a multi-product, multi-echelon supply chain case study, which is intended to cooperate or to compete with another SC of similar characteristics.
Fil: Zamarripa, Miguel A.. Universidad Politecnica de Catalunya; España
Fil: Aguirre, Adrian Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Espuña, Antonio. Universidad Politecnica de Catalunya; España
description This work proposes to improve the tactical decision-making of a supply chain (SC) under an uncertain competition scenario through the use of different optimization criteria, which allows to manage not only the specific objectives of the SC of interest, but also the way how its clients address their selection between different potential suppliers, identifying best market share for the SC of interest and the strategy to attain it. The resulting multi-objective optimization problem has been solved using the ɛ-constraint method in order to approximate the Pareto space of non-dominated solutions while a framework based on game theory is used as a reactive decision making support tool to deal with the uncertainty of the competitive scenario. The use of the proposed system is illustrated through its application to a multi-product, multi-echelon supply chain case study, which is intended to cooperate or to compete with another SC of similar characteristics.
publishDate 2013
dc.date.none.fl_str_mv 2013-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/8570
Zamarripa, Miguel A.; Aguirre, Adrian Marcelo; Mendez, Carlos Alberto; Espuña, Antonio; Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments; Inst Chemical Engineers; Chemical Engineering Research & Design; 91; 8; 6-2013; 1588-1600
0263-8762
url http://hdl.handle.net/11336/8570
identifier_str_mv Zamarripa, Miguel A.; Aguirre, Adrian Marcelo; Mendez, Carlos Alberto; Espuña, Antonio; Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments; Inst Chemical Engineers; Chemical Engineering Research & Design; 91; 8; 6-2013; 1588-1600
0263-8762
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cherd.2013.06.008
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0263876213002517
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Inst Chemical Engineers
publisher.none.fl_str_mv Inst Chemical Engineers
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842268625815207936
score 13.13397

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