Process Superstructure Optimization through Discrete Steepest Descent Optimization: a GDP Analysis and Applications in Process Intensification

This manuscript introduces a Logic-based Discrete-Steepest Descent Algorithm (LD- SDA) to tackle problems arising from process superstructure optimization. These problems often appear in Process Systems Engineering and become challenging when addressing Process Intensification applications. The curr...

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Vydáno v:Computer Aided Chemical Engineering Ročník 49; s. 1279 - 1284
Hlavní autoři: Bernal, David E., Ovalle, Daniel, Liñán, David A., Ricardez-Sandoval, Luis A., Gómez, Jorge M., Grossmann, Ignacio E.
Médium: Kapitola
Jazyk:angličtina
Vydáno: 2022
Témata:
convex discrete analysis
process intensification
superstructure optimization
superstructure optimization
convex discrete analysis
process intensification
ISBN:9780323851596, 0323851592
ISSN:1570-7946
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Abstract This manuscript introduces a Logic-based Discrete-Steepest Descent Algorithm (LD- SDA) to tackle problems arising from process superstructure optimization. These problems often appear in Process Systems Engineering and become challenging when addressing Process Intensification applications. The current algorithm considers a disjunctive interpretation of these optimization problems through Generalized Disjunctive Programming (GDP). This formulation allows further analysis of the solution method as a tailored approach for GDP and results in a general open-source implementation of the method relying on the modeling paradigm Pyomo.GDP. Complementing our previous studies in the subject, we compare the LD-SDA against other well-known GDP solution methods and a D-SDA that does not consider the disjunctive nature of these problems. The results showcase the advantages of LD-SDA when dealing with superstructure problems arising from process intensification.
AbstractList This manuscript introduces a Logic-based Discrete-Steepest Descent Algorithm (LD- SDA) to tackle problems arising from process superstructure optimization. These problems often appear in Process Systems Engineering and become challenging when addressing Process Intensification applications. The current algorithm considers a disjunctive interpretation of these optimization problems through Generalized Disjunctive Programming (GDP). This formulation allows further analysis of the solution method as a tailored approach for GDP and results in a general open-source implementation of the method relying on the modeling paradigm Pyomo.GDP. Complementing our previous studies in the subject, we compare the LD-SDA against other well-known GDP solution methods and a D-SDA that does not consider the disjunctive nature of these problems. The results showcase the advantages of LD-SDA when dealing with superstructure problems arising from process intensification.
Author Liñán, David A.
Gómez, Jorge M.
Bernal, David E.
Ricardez-Sandoval, Luis A.
Grossmann, Ignacio E.
Ovalle, Daniel
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  surname: Bernal
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  email: grossmann@cmu.edu
  organization: Department of Chemical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, United States of America
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  givenname: Daniel
  surname: Ovalle
  fullname: Ovalle, Daniel
  organization: Department of Chemical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, United States of America
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  givenname: David A.
  surname: Liñán
  fullname: Liñán, David A.
  organization: Department of Chemical Engineering, University of Waterloo, Ontario N2L 3G1, Canada
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  givenname: Luis A.
  surname: Ricardez-Sandoval
  fullname: Ricardez-Sandoval, Luis A.
  organization: Department of Chemical Engineering, University of Waterloo, Ontario N2L 3G1, Canada
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  givenname: Jorge M.
  surname: Gómez
  fullname: Gómez, Jorge M.
  organization: Departamento de Ingeniería Química y de Alimentos, Universidad de Los Andes, Bogotá 111711, Colombia
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  givenname: Ignacio E.
  surname: Grossmann
  fullname: Grossmann, Ignacio E.
  organization: Department of Chemical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, United States of America
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Keywords superstructure optimization
convex discrete analysis
process intensification
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Snippet This manuscript introduces a Logic-based Discrete-Steepest Descent Algorithm (LD- SDA) to tackle problems arising from process superstructure optimization....
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StartPage 1279
SubjectTerms convex discrete analysis
process intensification
superstructure optimization
Title Process Superstructure Optimization through Discrete Steepest Descent Optimization: a GDP Analysis and Applications in Process Intensification
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