Mathematical models for optimizing production chain planning in salmon farming

Autores
Bravo, Fernanda; Duran, Guillermo Alfredo; Lucena, Abilio; Marenco, Javier; Moran, Diego; Weintraub, Andres
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The salmon farming production chain is structured in four consecutive phases: freshwater, seawater, plant processing, and distribution and marketing. The phases interact in a pull manner, freshwater stocks fish to meet seawater's demand, seawater produces to meet plant processing biomass demand, and the processing plant produces to satisfy consumers' demand. Freshwater planning decisions are in regard to which freshwater center the fish should be located depending on the state of development of the fish. The goal is to satisfy seawater's demand while minimizing costs. In the seawater phase, the fish are first placed in seawater centers, and then sent to the processing plant as they approach suitable harvest conditions. The goal of seawater is to maximize harvested biomass while satisfying processing plant's demand. This paper presents two mixed-integer linear programming models—one for the freshwater phase and another for the seawater phase. These models are designed in such a way that the production planning is well integrated and more efficient and incorporates the requirements of the farm operator's freshwater and seawater units (biological, economic, and health-related constraints) ensuring that production in both phases is better coordinated. The development of the two models was based on the farming operations of one of the main producer farms in Chile. Preliminary evaluations of the models indicate that they not only succeed in enforcing constraints that are difficult to be met by manual planning but also led to more effective results in terms of the objectives set out.
Fil: Bravo, Fernanda. Massachusetts Institute of Technology; Estados Unidos. Universidad de Chile; Chile
Fil: Duran, Guillermo Alfredo. Universidad de Chile; Chile. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lucena, Abilio. Universidade Federal do Rio de Janeiro; Brasil
Fil: Marenco, Javier. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Fil: Moran, Diego. Universidad de Chile; Chile. Georgia Institute Of Techology; Estados Unidos
Fil: Weintraub, Andres. Universidad de Chile; Chile
Materia
Mathematical Programming
Integer Programming
Models
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/15803
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/15803
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Mathematical models for optimizing production chain planning in salmon farmingBravo, FernandaDuran, Guillermo AlfredoLucena, AbilioMarenco, JavierMoran, DiegoWeintraub, AndresMathematical ProgrammingInteger ProgrammingModelshttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1The salmon farming production chain is structured in four consecutive phases: freshwater, seawater, plant processing, and distribution and marketing. The phases interact in a pull manner, freshwater stocks fish to meet seawater's demand, seawater produces to meet plant processing biomass demand, and the processing plant produces to satisfy consumers' demand. Freshwater planning decisions are in regard to which freshwater center the fish should be located depending on the state of development of the fish. The goal is to satisfy seawater's demand while minimizing costs. In the seawater phase, the fish are first placed in seawater centers, and then sent to the processing plant as they approach suitable harvest conditions. The goal of seawater is to maximize harvested biomass while satisfying processing plant's demand. This paper presents two mixed-integer linear programming models—one for the freshwater phase and another for the seawater phase. These models are designed in such a way that the production planning is well integrated and more efficient and incorporates the requirements of the farm operator's freshwater and seawater units (biological, economic, and health-related constraints) ensuring that production in both phases is better coordinated. The development of the two models was based on the farming operations of one of the main producer farms in Chile. Preliminary evaluations of the models indicate that they not only succeed in enforcing constraints that are difficult to be met by manual planning but also led to more effective results in terms of the objectives set out.Fil: Bravo, Fernanda. Massachusetts Institute of Technology; Estados Unidos. Universidad de Chile; ChileFil: Duran, Guillermo Alfredo. Universidad de Chile; Chile. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lucena, Abilio. Universidade Federal do Rio de Janeiro; BrasilFil: Marenco, Javier. Universidad Nacional de General Sarmiento. Instituto de Ciencias; ArgentinaFil: Moran, Diego. Universidad de Chile; Chile. Georgia Institute Of Techology; Estados UnidosFil: Weintraub, Andres. Universidad de Chile; ChileWiley2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/15803Bravo, Fernanda; Duran, Guillermo Alfredo; Lucena, Abilio; Marenco, Javier; Moran, Diego; et al.; Mathematical models for optimizing production chain planning in salmon farming; Wiley; International Transactions In Operational Research; 20; 5; -1-2013; 731-7660969-6016enginfo:eu-repo/semantics/altIdentifier/doi/10.1111/itor.12022info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1111/itor.12022/abstractinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:51:32Zoai:ri.conicet.gov.ar:11336/15803instacron: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:34982025-09-29 09:51:33.209CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Mathematical models for optimizing production chain planning in salmon farming
title Mathematical models for optimizing production chain planning in salmon farming
spellingShingle Mathematical models for optimizing production chain planning in salmon farming
Bravo, Fernanda
Mathematical Programming
Integer Programming
Models
title_short Mathematical models for optimizing production chain planning in salmon farming
title_full Mathematical models for optimizing production chain planning in salmon farming
title_fullStr Mathematical models for optimizing production chain planning in salmon farming
title_full_unstemmed Mathematical models for optimizing production chain planning in salmon farming
title_sort Mathematical models for optimizing production chain planning in salmon farming
dc.creator.none.fl_str_mv Bravo, Fernanda
Duran, Guillermo Alfredo
Lucena, Abilio
Marenco, Javier
Moran, Diego
Weintraub, Andres
author Bravo, Fernanda
author_facet Bravo, Fernanda
Duran, Guillermo Alfredo
Lucena, Abilio
Marenco, Javier
Moran, Diego
Weintraub, Andres
author_role author
author2 Duran, Guillermo Alfredo
Lucena, Abilio
Marenco, Javier
Moran, Diego
Weintraub, Andres
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Mathematical Programming
Integer Programming
Models
topic Mathematical Programming
Integer Programming
Models
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The salmon farming production chain is structured in four consecutive phases: freshwater, seawater, plant processing, and distribution and marketing. The phases interact in a pull manner, freshwater stocks fish to meet seawater's demand, seawater produces to meet plant processing biomass demand, and the processing plant produces to satisfy consumers' demand. Freshwater planning decisions are in regard to which freshwater center the fish should be located depending on the state of development of the fish. The goal is to satisfy seawater's demand while minimizing costs. In the seawater phase, the fish are first placed in seawater centers, and then sent to the processing plant as they approach suitable harvest conditions. The goal of seawater is to maximize harvested biomass while satisfying processing plant's demand. This paper presents two mixed-integer linear programming models—one for the freshwater phase and another for the seawater phase. These models are designed in such a way that the production planning is well integrated and more efficient and incorporates the requirements of the farm operator's freshwater and seawater units (biological, economic, and health-related constraints) ensuring that production in both phases is better coordinated. The development of the two models was based on the farming operations of one of the main producer farms in Chile. Preliminary evaluations of the models indicate that they not only succeed in enforcing constraints that are difficult to be met by manual planning but also led to more effective results in terms of the objectives set out.
Fil: Bravo, Fernanda. Massachusetts Institute of Technology; Estados Unidos. Universidad de Chile; Chile
Fil: Duran, Guillermo Alfredo. Universidad de Chile; Chile. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lucena, Abilio. Universidade Federal do Rio de Janeiro; Brasil
Fil: Marenco, Javier. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Fil: Moran, Diego. Universidad de Chile; Chile. Georgia Institute Of Techology; Estados Unidos
Fil: Weintraub, Andres. Universidad de Chile; Chile
description The salmon farming production chain is structured in four consecutive phases: freshwater, seawater, plant processing, and distribution and marketing. The phases interact in a pull manner, freshwater stocks fish to meet seawater's demand, seawater produces to meet plant processing biomass demand, and the processing plant produces to satisfy consumers' demand. Freshwater planning decisions are in regard to which freshwater center the fish should be located depending on the state of development of the fish. The goal is to satisfy seawater's demand while minimizing costs. In the seawater phase, the fish are first placed in seawater centers, and then sent to the processing plant as they approach suitable harvest conditions. The goal of seawater is to maximize harvested biomass while satisfying processing plant's demand. This paper presents two mixed-integer linear programming models—one for the freshwater phase and another for the seawater phase. These models are designed in such a way that the production planning is well integrated and more efficient and incorporates the requirements of the farm operator's freshwater and seawater units (biological, economic, and health-related constraints) ensuring that production in both phases is better coordinated. The development of the two models was based on the farming operations of one of the main producer farms in Chile. Preliminary evaluations of the models indicate that they not only succeed in enforcing constraints that are difficult to be met by manual planning but also led to more effective results in terms of the objectives set out.
publishDate 2013
dc.date.none.fl_str_mv 2013
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/11336/15803
Bravo, Fernanda; Duran, Guillermo Alfredo; Lucena, Abilio; Marenco, Javier; Moran, Diego; et al.; Mathematical models for optimizing production chain planning in salmon farming; Wiley; International Transactions In Operational Research; 20; 5; -1-2013; 731-766
0969-6016
url http://hdl.handle.net/11336/15803
identifier_str_mv Bravo, Fernanda; Duran, Guillermo Alfredo; Lucena, Abilio; Marenco, Javier; Moran, Diego; et al.; Mathematical models for optimizing production chain planning in salmon farming; Wiley; International Transactions In Operational Research; 20; 5; -1-2013; 731-766
0969-6016
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1111/itor.12022
info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1111/itor.12022/abstract
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
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
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score 13.069144

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