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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/15803
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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 Técnicas2025-09-03T09:53:01Zoai: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:34982025-09-03 09:53:01.625CONICET 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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1842269196113674240 |
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13.13397 |