Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant
- Autores
- Rodriguez, Maria Analia; Montagna, Jorge Marcelo; Vecchietti, Aldo; Corsano, Gabriela
- Año de publicación
- 2017
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- A Generalized Disjunctive Programming (GDP) model for the optimal multi-period production planning and stock management is proposed in this work. The formulation is applied to a polyurethane foam manufacturing plant that comprises three stages: a first step that produces pieces with certain characteristics, a second process that involves the location of these pieces in a limited area and a third stage where pieces are stored in dedicated spaces. This article shows the GDP capabilities to provide a qualitative framework for representing the problem issues and their connections in a natural way, especially in a context where decisions integration is required. Due to the multi-period nature of the planning problem, a rolling horizon approach is suitable for solving it in reasonable computing time. It serves as a tool for analyzing the trade-offs among the different costs. Through the examples, the capabilities of the formulation and the proposed resolution method are highlighted.
Fil: Rodriguez, Maria Analia. 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: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina - Materia
-
Generalized Disjunctive Programming
Mattress Industry
Optimization
Production Planning
Rolling Horizon
Stock - 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:11336/38489
Ver los metadatos del registro completo
id |
CONICETDig_4915154a7110d6600ca5dda811ba515b |
---|---|
oai_identifier_str |
oai:ri.conicet.gov.ar:11336/38489 |
network_acronym_str |
CONICETDig |
repository_id_str |
3498 |
network_name_str |
CONICET Digital (CONICET) |
spelling |
Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plantRodriguez, Maria AnaliaMontagna, Jorge MarceloVecchietti, AldoCorsano, GabrielaGeneralized Disjunctive ProgrammingMattress IndustryOptimizationProduction PlanningRolling HorizonStockhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2A Generalized Disjunctive Programming (GDP) model for the optimal multi-period production planning and stock management is proposed in this work. The formulation is applied to a polyurethane foam manufacturing plant that comprises three stages: a first step that produces pieces with certain characteristics, a second process that involves the location of these pieces in a limited area and a third stage where pieces are stored in dedicated spaces. This article shows the GDP capabilities to provide a qualitative framework for representing the problem issues and their connections in a natural way, especially in a context where decisions integration is required. Due to the multi-period nature of the planning problem, a rolling horizon approach is suitable for solving it in reasonable computing time. It serves as a tool for analyzing the trade-offs among the different costs. Through the examples, the capabilities of the formulation and the proposed resolution method are highlighted.Fil: Rodriguez, Maria Analia. 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: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaPergamon-Elsevier Science Ltd2017-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/38489Rodriguez, Maria Analia; Montagna, Jorge Marcelo; Vecchietti, Aldo; Corsano, Gabriela; Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 103; 8-2017; 69-800098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2017.03.006info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0098135417301187info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:53:18Zoai:ri.conicet.gov.ar:11336/38489instacron: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 09:53:18.814CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant |
title |
Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant |
spellingShingle |
Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant Rodriguez, Maria Analia Generalized Disjunctive Programming Mattress Industry Optimization Production Planning Rolling Horizon Stock |
title_short |
Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant |
title_full |
Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant |
title_fullStr |
Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant |
title_full_unstemmed |
Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant |
title_sort |
Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant |
dc.creator.none.fl_str_mv |
Rodriguez, Maria Analia Montagna, Jorge Marcelo Vecchietti, Aldo Corsano, Gabriela |
author |
Rodriguez, Maria Analia |
author_facet |
Rodriguez, Maria Analia Montagna, Jorge Marcelo Vecchietti, Aldo Corsano, Gabriela |
author_role |
author |
author2 |
Montagna, Jorge Marcelo Vecchietti, Aldo Corsano, Gabriela |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
Generalized Disjunctive Programming Mattress Industry Optimization Production Planning Rolling Horizon Stock |
topic |
Generalized Disjunctive Programming Mattress Industry Optimization Production Planning Rolling Horizon Stock |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/2.4 https://purl.org/becyt/ford/2 |
dc.description.none.fl_txt_mv |
A Generalized Disjunctive Programming (GDP) model for the optimal multi-period production planning and stock management is proposed in this work. The formulation is applied to a polyurethane foam manufacturing plant that comprises three stages: a first step that produces pieces with certain characteristics, a second process that involves the location of these pieces in a limited area and a third stage where pieces are stored in dedicated spaces. This article shows the GDP capabilities to provide a qualitative framework for representing the problem issues and their connections in a natural way, especially in a context where decisions integration is required. Due to the multi-period nature of the planning problem, a rolling horizon approach is suitable for solving it in reasonable computing time. It serves as a tool for analyzing the trade-offs among the different costs. Through the examples, the capabilities of the formulation and the proposed resolution method are highlighted. Fil: Rodriguez, Maria Analia. 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: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina Fil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina |
description |
A Generalized Disjunctive Programming (GDP) model for the optimal multi-period production planning and stock management is proposed in this work. The formulation is applied to a polyurethane foam manufacturing plant that comprises three stages: a first step that produces pieces with certain characteristics, a second process that involves the location of these pieces in a limited area and a third stage where pieces are stored in dedicated spaces. This article shows the GDP capabilities to provide a qualitative framework for representing the problem issues and their connections in a natural way, especially in a context where decisions integration is required. Due to the multi-period nature of the planning problem, a rolling horizon approach is suitable for solving it in reasonable computing time. It serves as a tool for analyzing the trade-offs among the different costs. Through the examples, the capabilities of the formulation and the proposed resolution method are highlighted. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-08 |
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/11336/38489 Rodriguez, Maria Analia; Montagna, Jorge Marcelo; Vecchietti, Aldo; Corsano, Gabriela; Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 103; 8-2017; 69-80 0098-1354 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/38489 |
identifier_str_mv |
Rodriguez, Maria Analia; Montagna, Jorge Marcelo; Vecchietti, Aldo; Corsano, Gabriela; Generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 103; 8-2017; 69-80 0098-1354 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2017.03.006 info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0098135417301187 |
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 |
Pergamon-Elsevier Science Ltd |
publisher.none.fl_str_mv |
Pergamon-Elsevier Science Ltd |
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_ |
1842269215472484352 |
score |
13.13397 |