Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant

Autores
Durand, Guillermo Andrés; Moreno, Marta Susana; Mele, Fernando Daniel; Montagna, Jorge Marcelo; Bandoni, Jose Alberto
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
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 MixedInteger 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 multi-period 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 MILPproblem 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.
Fil: Durand, Guillermo Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Moreno, Marta Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Mele, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Nacional de Tucumán; Argentina
Fil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Materia
UNCERTAINTY
TWO-STAGE STOCHASTIC PROGRAMMING
SIMULATION-BASED OPTIMIZATION
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:11336/77394
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/77394
network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plantDurand, Guillermo AndrésMoreno, Marta SusanaMele, Fernando DanielMontagna, Jorge MarceloBandoni, Jose AlbertoUNCERTAINTYTWO-STAGE STOCHASTIC PROGRAMMINGSIMULATION-BASED OPTIMIZATIONhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2https://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1This 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 MixedInteger 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 multi-period 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 MILPproblem 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.Fil: Durand, Guillermo Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Moreno, Marta Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Mele, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Nacional de Tucumán; ArgentinaFil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaUniversidade Federal de Santa Catarina2013-10info: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/11336/77394Durand, Guillermo Andrés; Moreno, Marta Susana; Mele, Fernando Daniel; Montagna, Jorge Marcelo; Bandoni, Jose Alberto; Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant; Universidade Federal de Santa Catarina; Iberoamerican Journal of Industrial Engineering; 5; 10; 10-2013; 43-542175-8018CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://incubadora.periodicos.ufsc.br/index.php/IJIE/article/view/3044info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-12T09:57:26Zoai:ri.conicet.gov.ar:11336/77394instacron: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:34982025-11-12 09:57:26.625CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant
title Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant
spellingShingle Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant
Durand, Guillermo Andrés
UNCERTAINTY
TWO-STAGE STOCHASTIC PROGRAMMING
SIMULATION-BASED OPTIMIZATION
title_short Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant
title_full Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant
title_fullStr Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous 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 simultanenous design and planning of a multiproduct batch plant
title_sort Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant
dc.creator.none.fl_str_mv Durand, Guillermo Andrés
Moreno, Marta Susana
Mele, Fernando Daniel
Montagna, Jorge Marcelo
Bandoni, Jose Alberto
author Durand, Guillermo Andrés
author_facet Durand, Guillermo Andrés
Moreno, Marta Susana
Mele, Fernando Daniel
Montagna, Jorge Marcelo
Bandoni, Jose Alberto
author_role author
author2 Moreno, Marta Susana
Mele, Fernando Daniel
Montagna, Jorge Marcelo
Bandoni, Jose Alberto
author2_role author
author
author
author
dc.subject.none.fl_str_mv UNCERTAINTY
TWO-STAGE STOCHASTIC PROGRAMMING
SIMULATION-BASED OPTIMIZATION
topic UNCERTAINTY
TWO-STAGE STOCHASTIC PROGRAMMING
SIMULATION-BASED OPTIMIZATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
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 MixedInteger 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 multi-period 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 MILPproblem 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.
Fil: Durand, Guillermo Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Moreno, Marta Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Mele, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Nacional de Tucumán; Argentina
Fil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
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 MixedInteger 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 multi-period 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 MILPproblem 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 2013-10
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/11336/77394
Durand, Guillermo Andrés; Moreno, Marta Susana; Mele, Fernando Daniel; Montagna, Jorge Marcelo; Bandoni, Jose Alberto; Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant; Universidade Federal de Santa Catarina; Iberoamerican Journal of Industrial Engineering; 5; 10; 10-2013; 43-54
2175-8018
CONICET Digital
CONICET
url http://hdl.handle.net/11336/77394
identifier_str_mv Durand, Guillermo Andrés; Moreno, Marta Susana; Mele, Fernando Daniel; Montagna, Jorge Marcelo; Bandoni, Jose Alberto; Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultanenous design and planning of a multiproduct batch plant; Universidade Federal de Santa Catarina; Iberoamerican Journal of Industrial Engineering; 5; 10; 10-2013; 43-54
2175-8018
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://incubadora.periodicos.ufsc.br/index.php/IJIE/article/view/3044
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 Universidade Federal de Santa Catarina
publisher.none.fl_str_mv Universidade Federal de Santa Catarina
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 13.24909

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