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dc.contributor.author
Bravo, Fernanda  
dc.contributor.author
Duran, Guillermo Alfredo  
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Lucena, Abilio  
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Marenco, Javier  
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Moran, Diego  
dc.contributor.author
Weintraub, Andres  
dc.date.available
2017-04-27T17:17:49Z  
dc.date.issued
2013  
dc.identifier.citation
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  
dc.identifier.issn
0969-6016  
dc.identifier.uri
http://hdl.handle.net/11336/15803  
dc.description.abstract
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.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Wiley  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Mathematical Programming  
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Integer Programming  
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Models  
dc.subject.classification
Matemática Aplicada  
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Matemáticas  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
Mathematical models for optimizing production chain planning in salmon farming  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2017-04-24T14:49:05Z  
dc.journal.volume
20  
dc.journal.number
5  
dc.journal.pagination
731-766  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Hoboken  
dc.description.fil
Fil: Bravo, Fernanda. Massachusetts Institute of Technology; Estados Unidos. Universidad de Chile; Chile  
dc.description.fil
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  
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Fil: Lucena, Abilio. Universidade Federal do Rio de Janeiro; Brasil  
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Fil: Marenco, Javier. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina  
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Fil: Moran, Diego. Universidad de Chile; Chile. Georgia Institute Of Techology; Estados Unidos  
dc.description.fil
Fil: Weintraub, Andres. Universidad de Chile; Chile  
dc.journal.title
International Transactions In Operational Research  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1111/itor.12022  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1111/itor.12022/abstract