A three-stage stochastic optimization model for the Brazilian biodiesel supply chain

Detalhes bibliográficos
Autor(a) principal: Senna,Pedro
Data de Publicação: 2016
Outros Autores: Pinha,Denis, Ahluwalia,Rashpal, Guimarães,Julio Cesar, Severo,Eliana, Reis,Augusto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Production
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132016000300501
Resumo: Abstract The Brazilian program for biodiesel use highlights the production of biodiesel from castor seeds. Biodiesel is a non-polluting energy source that has the potential to promote prosperity by creating jobs in poor regions of Brazil. However, the infrastructure, logistics, and proper facilities are lacking. A variety of approaches to optimizing the biodiesel supply chain have been proposed. The goal is to minimize the grain storage and transportation costs. This paper presents a comparison between a two-stage model and a multistage (three-stage) stochastic model to optimize the biodiesel supply chain. The comparison between these formulations shows that the flexibility gain provided by the multistage model results in a lower total logistic cost. The optimum for the three-stage model was 7,700,019 (BRL), compared to 8,628,002 (BRL) for the two-stage model, representing a savings of 927,983 (BRL). We highlight that this model offers a real solution for castor supply chain design (considering uncertainty) in the Brazilian semiarid region, which is a poorer region of the country, thus making cost reduction mandatory.
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spelling A three-stage stochastic optimization model for the Brazilian biodiesel supply chainBiodieselMixed Integer Linear programmingStochastic optimizationMultistage programAbstract The Brazilian program for biodiesel use highlights the production of biodiesel from castor seeds. Biodiesel is a non-polluting energy source that has the potential to promote prosperity by creating jobs in poor regions of Brazil. However, the infrastructure, logistics, and proper facilities are lacking. A variety of approaches to optimizing the biodiesel supply chain have been proposed. The goal is to minimize the grain storage and transportation costs. This paper presents a comparison between a two-stage model and a multistage (three-stage) stochastic model to optimize the biodiesel supply chain. The comparison between these formulations shows that the flexibility gain provided by the multistage model results in a lower total logistic cost. The optimum for the three-stage model was 7,700,019 (BRL), compared to 8,628,002 (BRL) for the two-stage model, representing a savings of 927,983 (BRL). We highlight that this model offers a real solution for castor supply chain design (considering uncertainty) in the Brazilian semiarid region, which is a poorer region of the country, thus making cost reduction mandatory.Associação Brasileira de Engenharia de Produção2016-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132016000300501Production v.26 n.3 2016reponame:Productioninstname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPRO10.1590/0103-6513.200015info:eu-repo/semantics/openAccessSenna,PedroPinha,DenisAhluwalia,RashpalGuimarães,Julio CesarSevero,ElianaReis,Augustoeng2016-08-09T00:00:00Zoai:scielo:S0103-65132016000300501Revistahttps://www.scielo.br/j/prod/https://old.scielo.br/oai/scielo-oai.php||production@editoracubo.com.br1980-54110103-6513opendoar:2016-08-09T00:00Production - Associação Brasileira de Engenharia de Produção (ABEPRO)false
dc.title.none.fl_str_mv A three-stage stochastic optimization model for the Brazilian biodiesel supply chain
title A three-stage stochastic optimization model for the Brazilian biodiesel supply chain
spellingShingle A three-stage stochastic optimization model for the Brazilian biodiesel supply chain
Senna,Pedro
Biodiesel
Mixed Integer Linear programming
Stochastic optimization
Multistage program
title_short A three-stage stochastic optimization model for the Brazilian biodiesel supply chain
title_full A three-stage stochastic optimization model for the Brazilian biodiesel supply chain
title_fullStr A three-stage stochastic optimization model for the Brazilian biodiesel supply chain
title_full_unstemmed A three-stage stochastic optimization model for the Brazilian biodiesel supply chain
title_sort A three-stage stochastic optimization model for the Brazilian biodiesel supply chain
author Senna,Pedro
author_facet Senna,Pedro
Pinha,Denis
Ahluwalia,Rashpal
Guimarães,Julio Cesar
Severo,Eliana
Reis,Augusto
author_role author
author2 Pinha,Denis
Ahluwalia,Rashpal
Guimarães,Julio Cesar
Severo,Eliana
Reis,Augusto
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Senna,Pedro
Pinha,Denis
Ahluwalia,Rashpal
Guimarães,Julio Cesar
Severo,Eliana
Reis,Augusto
dc.subject.por.fl_str_mv Biodiesel
Mixed Integer Linear programming
Stochastic optimization
Multistage program
topic Biodiesel
Mixed Integer Linear programming
Stochastic optimization
Multistage program
description Abstract The Brazilian program for biodiesel use highlights the production of biodiesel from castor seeds. Biodiesel is a non-polluting energy source that has the potential to promote prosperity by creating jobs in poor regions of Brazil. However, the infrastructure, logistics, and proper facilities are lacking. A variety of approaches to optimizing the biodiesel supply chain have been proposed. The goal is to minimize the grain storage and transportation costs. This paper presents a comparison between a two-stage model and a multistage (three-stage) stochastic model to optimize the biodiesel supply chain. The comparison between these formulations shows that the flexibility gain provided by the multistage model results in a lower total logistic cost. The optimum for the three-stage model was 7,700,019 (BRL), compared to 8,628,002 (BRL) for the two-stage model, representing a savings of 927,983 (BRL). We highlight that this model offers a real solution for castor supply chain design (considering uncertainty) in the Brazilian semiarid region, which is a poorer region of the country, thus making cost reduction mandatory.
publishDate 2016
dc.date.none.fl_str_mv 2016-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132016000300501
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132016000300501
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0103-6513.200015
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Engenharia de Produção
publisher.none.fl_str_mv Associação Brasileira de Engenharia de Produção
dc.source.none.fl_str_mv Production v.26 n.3 2016
reponame:Production
instname:Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron:ABEPRO
instname_str Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron_str ABEPRO
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reponame_str Production
collection Production
repository.name.fl_str_mv Production - Associação Brasileira de Engenharia de Produção (ABEPRO)
repository.mail.fl_str_mv ||production@editoracubo.com.br
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