A bi-objective optimization model for tactical planning in the pome fruit industry supply chain

Autores
Catala, Luis Pedro; Moreno, Marta Susana; Blanco, Anibal Manuel; Bandoni, Jose Alberto
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work, a multi-period mixed integer linear programming formulation for the medium-term planning of the apples and pears supply chain is presented. Given the supply chain structure, demand data, and harvesting dates, the proposed approach integrates production, processing, distribution, and inventory decisions considering two conflicting objectives: profit and product supply shortage. The mathematical model is solved by using the lexicographic method to deal with the multi-objective optimization. The system is analyzed in the face of changes in storage, processing and transportation capacities. Major results indicate that in order to minimize supply shortage (leading objective) in the second part of the season, beneficial trade opportunities have to be missed along the year with the consequent reduction in the total profit (subordinated objective). To illustrate the approach, a pome fruit industry located in the “Alto Valle de Río Negro y Neuquén” Argentine region is considered as a case study.
Fil: Catala, Luis Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Moreno, Marta Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Blanco, Anibal Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Materia
Multi-Objective
Pome Fruit Industry
Supply Chain
Tactical Planning
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:11336/40031
Acceder
id CONICETDig_f2c4eb9325ef0093d91e3903aa65c6b8
oai_identifier_str oai:ri.conicet.gov.ar:11336/40031
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A bi-objective optimization model for tactical planning in the pome fruit industry supply chainCatala, Luis PedroMoreno, Marta SusanaBlanco, Anibal ManuelBandoni, Jose AlbertoMulti-ObjectivePome Fruit IndustrySupply ChainTactical Planninghttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1In this work, a multi-period mixed integer linear programming formulation for the medium-term planning of the apples and pears supply chain is presented. Given the supply chain structure, demand data, and harvesting dates, the proposed approach integrates production, processing, distribution, and inventory decisions considering two conflicting objectives: profit and product supply shortage. The mathematical model is solved by using the lexicographic method to deal with the multi-objective optimization. The system is analyzed in the face of changes in storage, processing and transportation capacities. Major results indicate that in order to minimize supply shortage (leading objective) in the second part of the season, beneficial trade opportunities have to be missed along the year with the consequent reduction in the total profit (subordinated objective). To illustrate the approach, a pome fruit industry located in the “Alto Valle de Río Negro y Neuquén” Argentine region is considered as a case study.Fil: Catala, Luis Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Moreno, Marta Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Blanco, Anibal Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaElsevier2016-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/40031Catala, Luis Pedro; Moreno, Marta Susana; Blanco, Anibal Manuel; Bandoni, Jose Alberto; A bi-objective optimization model for tactical planning in the pome fruit industry supply chain; Elsevier; Computers and Eletronics in Agriculture; 130; 11-2016; 128-1410168-1699CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0168169916309383info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compag.2016.10.008info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:48:20Zoai:ri.conicet.gov.ar:11336/40031instacron: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 09:48:20.671CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A bi-objective optimization model for tactical planning in the pome fruit industry supply chain
title A bi-objective optimization model for tactical planning in the pome fruit industry supply chain
spellingShingle A bi-objective optimization model for tactical planning in the pome fruit industry supply chain
Catala, Luis Pedro
Multi-Objective
Pome Fruit Industry
Supply Chain
Tactical Planning
title_short A bi-objective optimization model for tactical planning in the pome fruit industry supply chain
title_full A bi-objective optimization model for tactical planning in the pome fruit industry supply chain
title_fullStr A bi-objective optimization model for tactical planning in the pome fruit industry supply chain
title_full_unstemmed A bi-objective optimization model for tactical planning in the pome fruit industry supply chain
title_sort A bi-objective optimization model for tactical planning in the pome fruit industry supply chain
dc.creator.none.fl_str_mv Catala, Luis Pedro
Moreno, Marta Susana
Blanco, Anibal Manuel
Bandoni, Jose Alberto
author Catala, Luis Pedro
author_facet Catala, Luis Pedro
Moreno, Marta Susana
Blanco, Anibal Manuel
Bandoni, Jose Alberto
author_role author
author2 Moreno, Marta Susana
Blanco, Anibal Manuel
Bandoni, Jose Alberto
author2_role author
author
author
dc.subject.none.fl_str_mv Multi-Objective
Pome Fruit Industry
Supply Chain
Tactical Planning
topic Multi-Objective
Pome Fruit Industry
Supply Chain
Tactical Planning
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this work, a multi-period mixed integer linear programming formulation for the medium-term planning of the apples and pears supply chain is presented. Given the supply chain structure, demand data, and harvesting dates, the proposed approach integrates production, processing, distribution, and inventory decisions considering two conflicting objectives: profit and product supply shortage. The mathematical model is solved by using the lexicographic method to deal with the multi-objective optimization. The system is analyzed in the face of changes in storage, processing and transportation capacities. Major results indicate that in order to minimize supply shortage (leading objective) in the second part of the season, beneficial trade opportunities have to be missed along the year with the consequent reduction in the total profit (subordinated objective). To illustrate the approach, a pome fruit industry located in the “Alto Valle de Río Negro y Neuquén” Argentine region is considered as a case study.
Fil: Catala, Luis Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Moreno, Marta Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Blanco, Anibal Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
description In this work, a multi-period mixed integer linear programming formulation for the medium-term planning of the apples and pears supply chain is presented. Given the supply chain structure, demand data, and harvesting dates, the proposed approach integrates production, processing, distribution, and inventory decisions considering two conflicting objectives: profit and product supply shortage. The mathematical model is solved by using the lexicographic method to deal with the multi-objective optimization. The system is analyzed in the face of changes in storage, processing and transportation capacities. Major results indicate that in order to minimize supply shortage (leading objective) in the second part of the season, beneficial trade opportunities have to be missed along the year with the consequent reduction in the total profit (subordinated objective). To illustrate the approach, a pome fruit industry located in the “Alto Valle de Río Negro y Neuquén” Argentine region is considered as a case study.
publishDate 2016
dc.date.none.fl_str_mv 2016-11
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/11336/40031
Catala, Luis Pedro; Moreno, Marta Susana; Blanco, Anibal Manuel; Bandoni, Jose Alberto; A bi-objective optimization model for tactical planning in the pome fruit industry supply chain; Elsevier; Computers and Eletronics in Agriculture; 130; 11-2016; 128-141
0168-1699
CONICET Digital
CONICET
url http://hdl.handle.net/11336/40031
identifier_str_mv Catala, Luis Pedro; Moreno, Marta Susana; Blanco, Anibal Manuel; Bandoni, Jose Alberto; A bi-objective optimization model for tactical planning in the pome fruit industry supply chain; Elsevier; Computers and Eletronics in Agriculture; 130; 11-2016; 128-141
0168-1699
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0168169916309383
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compag.2016.10.008
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
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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_ 1842268919251861504
score 13.13397

Publicaciones similares