Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant
- Autores
- Durand, Guillermo; Moreno, M. Susana; Mele, Fernando D.; Montagna, Jorge Marcelo; Bandoni, Alberto
- Año de publicación
- 2013
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- This paper addresses the comparison between two techniques for the optimization under parametric uncertainty of multiproduct batch plants integrating design and production planning decisions. This problem has been conceived as a two-stage stochastic mixed integer linear programming (MILP) in which the first-stage decisions consist of design variables that allow determining the batch plant structure, and the second-stage decisions consist of production planning continuous variables in a multiperiod context. The objective function maximizes the expected net present value. In the first solving approach, the problem has been tackled through mathematical programming considering a discrete set of scenarios. In the second solving approach, the multi-scenario MILP problem has been reformulated by adopting a simulation-based optimization scheme to accommodate the variables belonging to different management levels. Advantages and disadvantages of both approaches are demonstrated through a case study. Results allow concluding that a simulation-based optimization strategy may be a suitable technique to afford two-stage stochastic programming problems.
Sociedad Argentina de Informática e Investigación Operativa - Materia
-
Ciencias Informáticas
Uncertainty
Two-stage stochastic programming
Simulation-based optimization - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/94333
Ver los metadatos del registro completo
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Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plantDurand, GuillermoMoreno, M. SusanaMele, Fernando D.Montagna, Jorge MarceloBandoni, AlbertoCiencias InformáticasUncertaintyTwo-stage stochastic programmingSimulation-based optimizationThis paper addresses the comparison between two techniques for the optimization under parametric uncertainty of multiproduct batch plants integrating design and production planning decisions. This problem has been conceived as a two-stage stochastic mixed integer linear programming (MILP) in which the first-stage decisions consist of design variables that allow determining the batch plant structure, and the second-stage decisions consist of production planning continuous variables in a multiperiod context. The objective function maximizes the expected net present value. In the first solving approach, the problem has been tackled through mathematical programming considering a discrete set of scenarios. In the second solving approach, the multi-scenario MILP problem has been reformulated by adopting a simulation-based optimization scheme to accommodate the variables belonging to different management levels. Advantages and disadvantages of both approaches are demonstrated through a case study. Results allow concluding that a simulation-based optimization strategy may be a suitable technique to afford two-stage stochastic programming problems.Sociedad Argentina de Informática e Investigación Operativa2013-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf94-104http://sedici.unlp.edu.ar/handle/10915/94333enginfo:eu-repo/semantics/altIdentifier/issn/2313-9102info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:51:53Zoai:sedici.unlp.edu.ar:10915/94333Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:51:54.352SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant |
title |
Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant |
spellingShingle |
Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant Durand, Guillermo Ciencias Informáticas Uncertainty Two-stage stochastic programming Simulation-based optimization |
title_short |
Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant |
title_full |
Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant |
title_fullStr |
Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant |
title_full_unstemmed |
Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant |
title_sort |
Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant |
dc.creator.none.fl_str_mv |
Durand, Guillermo Moreno, M. Susana Mele, Fernando D. Montagna, Jorge Marcelo Bandoni, Alberto |
author |
Durand, Guillermo |
author_facet |
Durand, Guillermo Moreno, M. Susana Mele, Fernando D. Montagna, Jorge Marcelo Bandoni, Alberto |
author_role |
author |
author2 |
Moreno, M. Susana Mele, Fernando D. Montagna, Jorge Marcelo Bandoni, Alberto |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Uncertainty Two-stage stochastic programming Simulation-based optimization |
topic |
Ciencias Informáticas Uncertainty Two-stage stochastic programming Simulation-based optimization |
dc.description.none.fl_txt_mv |
This paper addresses the comparison between two techniques for the optimization under parametric uncertainty of multiproduct batch plants integrating design and production planning decisions. This problem has been conceived as a two-stage stochastic mixed integer linear programming (MILP) in which the first-stage decisions consist of design variables that allow determining the batch plant structure, and the second-stage decisions consist of production planning continuous variables in a multiperiod context. The objective function maximizes the expected net present value. In the first solving approach, the problem has been tackled through mathematical programming considering a discrete set of scenarios. In the second solving approach, the multi-scenario MILP problem has been reformulated by adopting a simulation-based optimization scheme to accommodate the variables belonging to different management levels. Advantages and disadvantages of both approaches are demonstrated through a case study. Results allow concluding that a simulation-based optimization strategy may be a suitable technique to afford two-stage stochastic programming problems. Sociedad Argentina de Informática e Investigación Operativa |
description |
This paper addresses the comparison between two techniques for the optimization under parametric uncertainty of multiproduct batch plants integrating design and production planning decisions. This problem has been conceived as a two-stage stochastic mixed integer linear programming (MILP) in which the first-stage decisions consist of design variables that allow determining the batch plant structure, and the second-stage decisions consist of production planning continuous variables in a multiperiod context. The objective function maximizes the expected net present value. In the first solving approach, the problem has been tackled through mathematical programming considering a discrete set of scenarios. In the second solving approach, the multi-scenario MILP problem has been reformulated by adopting a simulation-based optimization scheme to accommodate the variables belonging to different management levels. Advantages and disadvantages of both approaches are demonstrated through a case study. Results allow concluding that a simulation-based optimization strategy may be a suitable technique to afford two-stage stochastic programming problems. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-09 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/94333 |
url |
http://sedici.unlp.edu.ar/handle/10915/94333 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/issn/2313-9102 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 94-104 |
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