Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems

Autores
Castro, Pedro M.; Aguirre, Adrian Marcelo; Zeballos, Luis Javier; Mendez, Carlos Alberto
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This article presents a new algorithm for industrially sized problems that, because of the large number of tasks to schedule, are either intractable or result in poor solutions when solved with full-space mathematical programming approaches. Focus is set on a special type of multistage batch plant featuring a single unit per stage, zero-wait storage policies, and a single transportation device for moving lots between stages. The algorithm incorporates a mixed-integer linear programming (MILP) continuous-time formulation and a discrete-event simulation model to generate a detailed schedule. More precisely, three stages are involved: (i) finding the best processing sequence, assuming that the transportation device is always available; (ii) generating a feasible schedule, taking into account the shared transportation resource; (iii) improving the schedule through a neighborhood search procedure. Relaxed and constrained versions of the full-space MILP are involved in stages (i) and (iii) with the simulation model taking care of stage (ii). Several examples are solved to illustrate the capabilities of the proposed method with the results showing better performance when compared to other published approaches. The balance between solution quality and total computational effort can easily be shifted by changing the number of lots rescheduled per iteration.
Fil: Castro, Pedro M.. Laboratorio Nacional de Energia e Geologia; Portugal
Fil: Aguirre, Adrian Marcelo. 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: Zeballos, Luis Javier. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
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
Materia
OPTIMIZATION
MIXED-INTEGER LINEAR PROGRAMMING
SHORT-TERM SCHEDULING
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:11336/238952
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling ProblemsCastro, Pedro M.Aguirre, Adrian MarceloZeballos, Luis JavierMendez, Carlos AlbertoOPTIMIZATIONMIXED-INTEGER LINEAR PROGRAMMINGSHORT-TERM SCHEDULINGhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2This article presents a new algorithm for industrially sized problems that, because of the large number of tasks to schedule, are either intractable or result in poor solutions when solved with full-space mathematical programming approaches. Focus is set on a special type of multistage batch plant featuring a single unit per stage, zero-wait storage policies, and a single transportation device for moving lots between stages. The algorithm incorporates a mixed-integer linear programming (MILP) continuous-time formulation and a discrete-event simulation model to generate a detailed schedule. More precisely, three stages are involved: (i) finding the best processing sequence, assuming that the transportation device is always available; (ii) generating a feasible schedule, taking into account the shared transportation resource; (iii) improving the schedule through a neighborhood search procedure. Relaxed and constrained versions of the full-space MILP are involved in stages (i) and (iii) with the simulation model taking care of stage (ii). Several examples are solved to illustrate the capabilities of the proposed method with the results showing better performance when compared to other published approaches. The balance between solution quality and total computational effort can easily be shifted by changing the number of lots rescheduled per iteration.Fil: Castro, Pedro M.. Laboratorio Nacional de Energia e Geologia; PortugalFil: Aguirre, Adrian Marcelo. 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: Zeballos, Luis Javier. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: 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; ArgentinaAmerican Chemical Society2011-08info: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/11336/238952Castro, Pedro M.; Aguirre, Adrian Marcelo; Zeballos, Luis Javier; Mendez, Carlos Alberto; Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems; American Chemical Society; Industrial & Engineering Chemical Research; 50; 18; 8-2011; 10665-106800888-5885CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://pubs.acs.org/doi/abs/10.1021/ie200841ainfo:eu-repo/semantics/altIdentifier/doi/10.1021/ie200841ainfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:13:00Zoai:ri.conicet.gov.ar:11336/238952instacron: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:34982025-09-29 10:13:00.956CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems
title Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems
spellingShingle Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems
Castro, Pedro M.
OPTIMIZATION
MIXED-INTEGER LINEAR PROGRAMMING
SHORT-TERM SCHEDULING
title_short Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems
title_full Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems
title_fullStr Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems
title_full_unstemmed Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems
title_sort Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems
dc.creator.none.fl_str_mv Castro, Pedro M.
Aguirre, Adrian Marcelo
Zeballos, Luis Javier
Mendez, Carlos Alberto
author Castro, Pedro M.
author_facet Castro, Pedro M.
Aguirre, Adrian Marcelo
Zeballos, Luis Javier
Mendez, Carlos Alberto
author_role author
author2 Aguirre, Adrian Marcelo
Zeballos, Luis Javier
Mendez, Carlos Alberto
author2_role author
author
author
dc.subject.none.fl_str_mv OPTIMIZATION
MIXED-INTEGER LINEAR PROGRAMMING
SHORT-TERM SCHEDULING
topic OPTIMIZATION
MIXED-INTEGER LINEAR PROGRAMMING
SHORT-TERM SCHEDULING
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 article presents a new algorithm for industrially sized problems that, because of the large number of tasks to schedule, are either intractable or result in poor solutions when solved with full-space mathematical programming approaches. Focus is set on a special type of multistage batch plant featuring a single unit per stage, zero-wait storage policies, and a single transportation device for moving lots between stages. The algorithm incorporates a mixed-integer linear programming (MILP) continuous-time formulation and a discrete-event simulation model to generate a detailed schedule. More precisely, three stages are involved: (i) finding the best processing sequence, assuming that the transportation device is always available; (ii) generating a feasible schedule, taking into account the shared transportation resource; (iii) improving the schedule through a neighborhood search procedure. Relaxed and constrained versions of the full-space MILP are involved in stages (i) and (iii) with the simulation model taking care of stage (ii). Several examples are solved to illustrate the capabilities of the proposed method with the results showing better performance when compared to other published approaches. The balance between solution quality and total computational effort can easily be shifted by changing the number of lots rescheduled per iteration.
Fil: Castro, Pedro M.. Laboratorio Nacional de Energia e Geologia; Portugal
Fil: Aguirre, Adrian Marcelo. 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: Zeballos, Luis Javier. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
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
description This article presents a new algorithm for industrially sized problems that, because of the large number of tasks to schedule, are either intractable or result in poor solutions when solved with full-space mathematical programming approaches. Focus is set on a special type of multistage batch plant featuring a single unit per stage, zero-wait storage policies, and a single transportation device for moving lots between stages. The algorithm incorporates a mixed-integer linear programming (MILP) continuous-time formulation and a discrete-event simulation model to generate a detailed schedule. More precisely, three stages are involved: (i) finding the best processing sequence, assuming that the transportation device is always available; (ii) generating a feasible schedule, taking into account the shared transportation resource; (iii) improving the schedule through a neighborhood search procedure. Relaxed and constrained versions of the full-space MILP are involved in stages (i) and (iii) with the simulation model taking care of stage (ii). Several examples are solved to illustrate the capabilities of the proposed method with the results showing better performance when compared to other published approaches. The balance between solution quality and total computational effort can easily be shifted by changing the number of lots rescheduled per iteration.
publishDate 2011
dc.date.none.fl_str_mv 2011-08
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/11336/238952
Castro, Pedro M.; Aguirre, Adrian Marcelo; Zeballos, Luis Javier; Mendez, Carlos Alberto; Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems; American Chemical Society; Industrial & Engineering Chemical Research; 50; 18; 8-2011; 10665-10680
0888-5885
CONICET Digital
CONICET
url http://hdl.handle.net/11336/238952
identifier_str_mv Castro, Pedro M.; Aguirre, Adrian Marcelo; Zeballos, Luis Javier; Mendez, Carlos Alberto; Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems; American Chemical Society; Industrial & Engineering Chemical Research; 50; 18; 8-2011; 10665-10680
0888-5885
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://pubs.acs.org/doi/abs/10.1021/ie200841a
info:eu-repo/semantics/altIdentifier/doi/10.1021/ie200841a
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
application/pdf
dc.publisher.none.fl_str_mv American Chemical Society
publisher.none.fl_str_mv American Chemical Society
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 13.069144

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