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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/238952
Ver los metadatos del registro completo
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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 Técnicas2025-09-03T10:00:43Zoai: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:34982025-09-03 10:00:43.481CONICET 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 |
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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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13.13397 |