Scope for industrial applications of production scheduling and solution methods

Autores
Harjunkoski, Iiro; Maravelias, Christos; Bongersc, Peter; Castro, Pedro; Engell, Sebastian; Grossmann, Ignacio; Hooker, John; Mendez, Carlos Alberto; Sand, Guido; Wassick, John
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper gives a review on existing scheduling methodologies developed for process industries. Above all, the aim of the paper is to focus on the industrial aspects of scheduling and discuss the main characteristics, including strengths and weaknesses of the presented approaches. It is claimed that optimization tools of today can effectively support the plant level production. However there is still clear potential for improvements, especially in transferring academic results into industry. For instance, usability, interfacing and integration are some aspects discussed in the paper. After the introduction and problem classification, the paper discusses some lessons learned from industry, provides an overview of models and methods and concludes with general guidelines and examples on the modeling and solution of industrial problems.
Fil: Harjunkoski, Iiro. ABB Corporate Research; Alemania
Fil: Maravelias, Christos. University Of Wisconsin; Estados Unidos
Fil: Bongersc, Peter. Eindhoven University of Technology; Países Bajos
Fil: Castro, Pedro. Laboratório Nacional de Energia e Geologia; Portugal
Fil: Engell, Sebastian. Universitat Dortmund; Alemania
Fil: Grossmann, Ignacio. University Of Carnegie Mellon; Estados Unidos
Fil: Hooker, John. University Of Carnegie Mellon; Estados Unidos
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina
Fil: Sand, Guido. ABB Corporate Research; Alemania
Fil: Wassick, John. The Dow Chemical Company; Estados Unidos
Materia
Scheduling
Optimization
Modeling
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:11336/9327
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Scope for industrial applications of production scheduling and solution methodsHarjunkoski, IiroMaravelias, ChristosBongersc, PeterCastro, PedroEngell, SebastianGrossmann, IgnacioHooker, JohnMendez, Carlos AlbertoSand, GuidoWassick, JohnSchedulingOptimizationModelinghttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2This paper gives a review on existing scheduling methodologies developed for process industries. Above all, the aim of the paper is to focus on the industrial aspects of scheduling and discuss the main characteristics, including strengths and weaknesses of the presented approaches. It is claimed that optimization tools of today can effectively support the plant level production. However there is still clear potential for improvements, especially in transferring academic results into industry. For instance, usability, interfacing and integration are some aspects discussed in the paper. After the introduction and problem classification, the paper discusses some lessons learned from industry, provides an overview of models and methods and concludes with general guidelines and examples on the modeling and solution of industrial problems.Fil: Harjunkoski, Iiro. ABB Corporate Research; AlemaniaFil: Maravelias, Christos. University Of Wisconsin; Estados UnidosFil: Bongersc, Peter. Eindhoven University of Technology; Países BajosFil: Castro, Pedro. Laboratório Nacional de Energia e Geologia; PortugalFil: Engell, Sebastian. Universitat Dortmund; AlemaniaFil: Grossmann, Ignacio. University Of Carnegie Mellon; Estados UnidosFil: Hooker, John. University Of Carnegie Mellon; Estados UnidosFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); ArgentinaFil: Sand, Guido. ABB Corporate Research; AlemaniaFil: Wassick, John. The Dow Chemical Company; Estados UnidosElsevier2014-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/9327Harjunkoski, Iiro; Maravelias, Christos; Bongersc, Peter; Castro, Pedro; Engell, Sebastian; et al.; Scope for industrial applications of production scheduling and solution methods; Elsevier; Computers And Chemical Engineering; 62; 10-2014; 161-1930098-1354enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2013.12.001info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135413003682info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:02:20Zoai:ri.conicet.gov.ar:11336/9327instacron: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 10:02:20.876CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Scope for industrial applications of production scheduling and solution methods
title Scope for industrial applications of production scheduling and solution methods
spellingShingle Scope for industrial applications of production scheduling and solution methods
Harjunkoski, Iiro
Scheduling
Optimization
Modeling
title_short Scope for industrial applications of production scheduling and solution methods
title_full Scope for industrial applications of production scheduling and solution methods
title_fullStr Scope for industrial applications of production scheduling and solution methods
title_full_unstemmed Scope for industrial applications of production scheduling and solution methods
title_sort Scope for industrial applications of production scheduling and solution methods
dc.creator.none.fl_str_mv Harjunkoski, Iiro
Maravelias, Christos
Bongersc, Peter
Castro, Pedro
Engell, Sebastian
Grossmann, Ignacio
Hooker, John
Mendez, Carlos Alberto
Sand, Guido
Wassick, John
author Harjunkoski, Iiro
author_facet Harjunkoski, Iiro
Maravelias, Christos
Bongersc, Peter
Castro, Pedro
Engell, Sebastian
Grossmann, Ignacio
Hooker, John
Mendez, Carlos Alberto
Sand, Guido
Wassick, John
author_role author
author2 Maravelias, Christos
Bongersc, Peter
Castro, Pedro
Engell, Sebastian
Grossmann, Ignacio
Hooker, John
Mendez, Carlos Alberto
Sand, Guido
Wassick, John
author2_role author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Scheduling
Optimization
Modeling
topic Scheduling
Optimization
Modeling
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This paper gives a review on existing scheduling methodologies developed for process industries. Above all, the aim of the paper is to focus on the industrial aspects of scheduling and discuss the main characteristics, including strengths and weaknesses of the presented approaches. It is claimed that optimization tools of today can effectively support the plant level production. However there is still clear potential for improvements, especially in transferring academic results into industry. For instance, usability, interfacing and integration are some aspects discussed in the paper. After the introduction and problem classification, the paper discusses some lessons learned from industry, provides an overview of models and methods and concludes with general guidelines and examples on the modeling and solution of industrial problems.
Fil: Harjunkoski, Iiro. ABB Corporate Research; Alemania
Fil: Maravelias, Christos. University Of Wisconsin; Estados Unidos
Fil: Bongersc, Peter. Eindhoven University of Technology; Países Bajos
Fil: Castro, Pedro. Laboratório Nacional de Energia e Geologia; Portugal
Fil: Engell, Sebastian. Universitat Dortmund; Alemania
Fil: Grossmann, Ignacio. University Of Carnegie Mellon; Estados Unidos
Fil: Hooker, John. University Of Carnegie Mellon; Estados Unidos
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina
Fil: Sand, Guido. ABB Corporate Research; Alemania
Fil: Wassick, John. The Dow Chemical Company; Estados Unidos
description This paper gives a review on existing scheduling methodologies developed for process industries. Above all, the aim of the paper is to focus on the industrial aspects of scheduling and discuss the main characteristics, including strengths and weaknesses of the presented approaches. It is claimed that optimization tools of today can effectively support the plant level production. However there is still clear potential for improvements, especially in transferring academic results into industry. For instance, usability, interfacing and integration are some aspects discussed in the paper. After the introduction and problem classification, the paper discusses some lessons learned from industry, provides an overview of models and methods and concludes with general guidelines and examples on the modeling and solution of industrial problems.
publishDate 2014
dc.date.none.fl_str_mv 2014-10
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/11336/9327
Harjunkoski, Iiro; Maravelias, Christos; Bongersc, Peter; Castro, Pedro; Engell, Sebastian; et al.; Scope for industrial applications of production scheduling and solution methods; Elsevier; Computers And Chemical Engineering; 62; 10-2014; 161-193
0098-1354
url http://hdl.handle.net/11336/9327
identifier_str_mv Harjunkoski, Iiro; Maravelias, Christos; Bongersc, Peter; Castro, Pedro; Engell, Sebastian; et al.; Scope for industrial applications of production scheduling and solution methods; Elsevier; Computers And Chemical Engineering; 62; 10-2014; 161-193
0098-1354
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.2013.12.001
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135413003682
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
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_ 1842269751826448384
score 13.13397

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