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

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 t...

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Autores principales: Durand, Guillermo, Moreno, M. Susana, Mele, Fernando D., Montagna, Jorge Marcelo, Bandoni, Alberto
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2013
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Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/94333
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id I19-R120-10915-94333
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Uncertainty
Two-stage stochastic programming
Simulation-based optimization
spellingShingle Ciencias Informáticas
Uncertainty
Two-stage stochastic programming
Simulation-based optimization
Durand, Guillermo
Moreno, M. Susana
Mele, Fernando D.
Montagna, Jorge Marcelo
Bandoni, Alberto
Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant
topic_facet Ciencias Informáticas
Uncertainty
Two-stage stochastic programming
Simulation-based optimization
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.
format Objeto de conferencia
Objeto de conferencia
author Durand, Guillermo
Moreno, M. Susana
Mele, Fernando D.
Montagna, Jorge Marcelo
Bandoni, Alberto
author_facet Durand, Guillermo
Moreno, M. Susana
Mele, Fernando D.
Montagna, Jorge Marcelo
Bandoni, Alberto
author_sort Durand, Guillermo
title Comparing the performances of two techniques for the optimization under parametric uncertainty of the simultaneous design and planning of a multiproduct batch plant
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
publishDate 2013
url http://sedici.unlp.edu.ar/handle/10915/94333
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