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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Bibliographic Details
Published inComputer Aided Chemical Engineering Vol. 49; pp. 1279 - 1284
Main Authors Bernal, David E., Ovalle, Daniel, Liñán, David A., Ricardez-Sandoval, Luis A., Gómez, Jorge M., Grossmann, Ignacio E.
Format Book Chapter
LanguageEnglish
Published 2022
Subjects
convex discrete analysis
process intensification
superstructure optimization
superstructure optimization
convex discrete analysis
process intensification
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Summary: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.
ISBN:9780323851596
0323851592
ISSN:1570-7946
DOI:10.1016/B978-0-323-85159-6.50213-X