State-of-the-art review of optimization methods for short-term scheduling of batch processes

Autores
Mendez, Carlos Alberto; Cerda, Jaime; Grossmann, Ignacio E.; Harjunkoski, Iiro; Fahl, M.
Año de publicación
2006
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
There has been significant progress in the area of short-term scheduling of batch processes, including the solution of industrial-sized problems, inthe last 20 years. The main goal of this paper is to provide an up-to-date reviewof the state-of-the-art in this challenging area. Main features, strengths and limitations of existing modeling and optimization techniques as well as other available major solution methods are examined through this paper. We first present a general classification for scheduling problems of batch processes as well as for the corresponding optimization models. Subsequently, the modeling of representative optimization approaches for the different problem types are introduced in detail, focusing on both discrete and continuous time models. A comparison of effectiveness and efficiency of these models is given for two benchmarking examples from the literature. We also discuss two real-world applications of scheduling problems that cannot be readily accommodated using existing methods. For the sake of completeness, other alternative solution methods applied in the field of scheduling are also reviewed, followed by a discussion related to solving large-scale problems through rigorous optimization approaches. Finally,we list available academic and commercial software, and briefly address the issue of rescheduling capabilities of the various optimization approaches as well as important extensions that go beyond short-term batch scheduling.
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina. University Of Carnegie Mellon; Estados Unidos
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Grossmann, Ignacio E.. University Of Carnegie Mellon; Estados Unidos
Fil: Harjunkoski, Iiro. ABB Corporate Research Center; Alemania
Fil: Fahl, M.. ABB Corporate Research Center; Alemania
Materia
Short-Term Scheduling
Optimization Models
Batch Processes
Milp
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/26403
Acceder
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network_name_str CONICET Digital (CONICET)
spelling State-of-the-art review of optimization methods for short-term scheduling of batch processesMendez, Carlos AlbertoCerda, JaimeGrossmann, Ignacio E.Harjunkoski, IiroFahl, M.Short-Term SchedulingOptimization ModelsBatch ProcessesMilphttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2There has been significant progress in the area of short-term scheduling of batch processes, including the solution of industrial-sized problems, inthe last 20 years. The main goal of this paper is to provide an up-to-date reviewof the state-of-the-art in this challenging area. Main features, strengths and limitations of existing modeling and optimization techniques as well as other available major solution methods are examined through this paper. We first present a general classification for scheduling problems of batch processes as well as for the corresponding optimization models. Subsequently, the modeling of representative optimization approaches for the different problem types are introduced in detail, focusing on both discrete and continuous time models. A comparison of effectiveness and efficiency of these models is given for two benchmarking examples from the literature. We also discuss two real-world applications of scheduling problems that cannot be readily accommodated using existing methods. For the sake of completeness, other alternative solution methods applied in the field of scheduling are also reviewed, followed by a discussion related to solving large-scale problems through rigorous optimization approaches. Finally,we list available academic and commercial software, and briefly address the issue of rescheduling capabilities of the various optimization approaches as well as important extensions that go beyond short-term batch scheduling.Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina. University Of Carnegie Mellon; Estados UnidosFil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Grossmann, Ignacio E.. University Of Carnegie Mellon; Estados UnidosFil: Harjunkoski, Iiro. ABB Corporate Research Center; AlemaniaFil: Fahl, M.. ABB Corporate Research Center; AlemaniaElsevier2006-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/26403Mendez, Carlos Alberto; Cerda, Jaime; Grossmann, Ignacio E.; Harjunkoski, Iiro; Fahl, M.; State-of-the-art review of optimization methods for short-term scheduling of batch processes; Elsevier; Computers and Chemical Engineering; 30; 6-7; 12-2006; 913-9460098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2006.02.008info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135406000287info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:11:27Zoai:ri.conicet.gov.ar:11336/26403instacron: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 10:11:27.812CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv State-of-the-art review of optimization methods for short-term scheduling of batch processes
title State-of-the-art review of optimization methods for short-term scheduling of batch processes
spellingShingle State-of-the-art review of optimization methods for short-term scheduling of batch processes
Mendez, Carlos Alberto
Short-Term Scheduling
Optimization Models
Batch Processes
Milp
title_short State-of-the-art review of optimization methods for short-term scheduling of batch processes
title_full State-of-the-art review of optimization methods for short-term scheduling of batch processes
title_fullStr State-of-the-art review of optimization methods for short-term scheduling of batch processes
title_full_unstemmed State-of-the-art review of optimization methods for short-term scheduling of batch processes
title_sort State-of-the-art review of optimization methods for short-term scheduling of batch processes
dc.creator.none.fl_str_mv Mendez, Carlos Alberto
Cerda, Jaime
Grossmann, Ignacio E.
Harjunkoski, Iiro
Fahl, M.
author Mendez, Carlos Alberto
author_facet Mendez, Carlos Alberto
Cerda, Jaime
Grossmann, Ignacio E.
Harjunkoski, Iiro
Fahl, M.
author_role author
author2 Cerda, Jaime
Grossmann, Ignacio E.
Harjunkoski, Iiro
Fahl, M.
author2_role author
author
author
author
dc.subject.none.fl_str_mv Short-Term Scheduling
Optimization Models
Batch Processes
Milp
topic Short-Term Scheduling
Optimization Models
Batch Processes
Milp
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv There has been significant progress in the area of short-term scheduling of batch processes, including the solution of industrial-sized problems, inthe last 20 years. The main goal of this paper is to provide an up-to-date reviewof the state-of-the-art in this challenging area. Main features, strengths and limitations of existing modeling and optimization techniques as well as other available major solution methods are examined through this paper. We first present a general classification for scheduling problems of batch processes as well as for the corresponding optimization models. Subsequently, the modeling of representative optimization approaches for the different problem types are introduced in detail, focusing on both discrete and continuous time models. A comparison of effectiveness and efficiency of these models is given for two benchmarking examples from the literature. We also discuss two real-world applications of scheduling problems that cannot be readily accommodated using existing methods. For the sake of completeness, other alternative solution methods applied in the field of scheduling are also reviewed, followed by a discussion related to solving large-scale problems through rigorous optimization approaches. Finally,we list available academic and commercial software, and briefly address the issue of rescheduling capabilities of the various optimization approaches as well as important extensions that go beyond short-term batch scheduling.
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina. University Of Carnegie Mellon; Estados Unidos
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Grossmann, Ignacio E.. University Of Carnegie Mellon; Estados Unidos
Fil: Harjunkoski, Iiro. ABB Corporate Research Center; Alemania
Fil: Fahl, M.. ABB Corporate Research Center; Alemania
description There has been significant progress in the area of short-term scheduling of batch processes, including the solution of industrial-sized problems, inthe last 20 years. The main goal of this paper is to provide an up-to-date reviewof the state-of-the-art in this challenging area. Main features, strengths and limitations of existing modeling and optimization techniques as well as other available major solution methods are examined through this paper. We first present a general classification for scheduling problems of batch processes as well as for the corresponding optimization models. Subsequently, the modeling of representative optimization approaches for the different problem types are introduced in detail, focusing on both discrete and continuous time models. A comparison of effectiveness and efficiency of these models is given for two benchmarking examples from the literature. We also discuss two real-world applications of scheduling problems that cannot be readily accommodated using existing methods. For the sake of completeness, other alternative solution methods applied in the field of scheduling are also reviewed, followed by a discussion related to solving large-scale problems through rigorous optimization approaches. Finally,we list available academic and commercial software, and briefly address the issue of rescheduling capabilities of the various optimization approaches as well as important extensions that go beyond short-term batch scheduling.
publishDate 2006
dc.date.none.fl_str_mv 2006-12
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/11336/26403
Mendez, Carlos Alberto; Cerda, Jaime; Grossmann, Ignacio E.; Harjunkoski, Iiro; Fahl, M.; State-of-the-art review of optimization methods for short-term scheduling of batch processes; Elsevier; Computers and Chemical Engineering; 30; 6-7; 12-2006; 913-946
0098-1354
CONICET Digital
CONICET
url http://hdl.handle.net/11336/26403
identifier_str_mv Mendez, Carlos Alberto; Cerda, Jaime; Grossmann, Ignacio E.; Harjunkoski, Iiro; Fahl, M.; State-of-the-art review of optimization methods for short-term scheduling of batch processes; Elsevier; Computers and Chemical Engineering; 30; 6-7; 12-2006; 913-946
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.2006.02.008
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135406000287
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
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
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score 13.13397

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