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dc.contributor.author
Raspanti, Claudia Gabriela
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dc.contributor.author
Bandoni, Jose Alberto
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dc.contributor.author
Biegler, L.
dc.date.available
2020-03-30T20:09:30Z
dc.date.issued
2000-10
dc.identifier.citation
Raspanti, Claudia Gabriela; Bandoni, Jose Alberto; Biegler, L.; New strategies for flexibility analysis and design under uncertainty; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 24; 9-10; 10-2000; 2193-2209
dc.identifier.issn
0098-1354
dc.identifier.uri
http://hdl.handle.net/11336/101422
dc.description.abstract
Process flexibility and design under uncertainty have been researched extensively in the literature. Problem formulations for flexibility include nested optimization problems and these can often be refined by substituting the optimality conditions for these nested problems. However, these reformulations are highly constrained and can be expensive to solve. In this paper we extend algorithms to solve these reformulated NLP problem under uncertainty by introducing two contributions to this approach. These are the use of a Constraint Aggregation function (KS function) and Smoothing Functions. We begin with basic properties of KS function. Next, we review a class of parametric smooth functions, used to replace the complementarity conditions of the KKT conditions with a well-behaved, smoothed nonlinear equality constraint. In this paper we apply the previous strategies to two specific problems: i) the'worst case algorithm', that assesses design under uncertainty and, ii) the flexibility index and feasibility test formulations. In the first case, two new algorithms are derived, one of them being single level optimization problem. Next using similar ideas, both flexibility index and feasibility test are reformulated leading to a single non linear programming problem instead of a mixed integer non linear programming one. The new formulations are demonstrated on five different example problems where a CPU time reduction of more than 70 and 80% is demonstrated.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Uncertainty
dc.subject
Design
dc.subject.classification
Ingeniería de Procesos Químicos
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dc.subject.classification
Ingeniería Química
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dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
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dc.title
New strategies for flexibility analysis and design under uncertainty
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2020-03-25T14:36:19Z
dc.journal.volume
24
dc.journal.number
9-10
dc.journal.pagination
2193-2209
dc.journal.pais
Países Bajos
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dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Raspanti, Claudia Gabriela. 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
dc.description.fil
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
dc.description.fil
Fil: Biegler, L.. Carnegie Mellon University; Estados Unidos
dc.journal.title
Computers and Chemical Engineering
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0098135400005913
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/S0098-1354(00)00591-3
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