Process superstructure optimization through discrete steepest descent optimization: a GDP analysis and applications in process intensificationShow others and affiliations
2022 (English)In: Computer Aided Chemical Engineering, Elsevier BV , 2022, Vol. 49, p. 1279-1284Conference paper, Published paper (Refereed)
Abstract [en]
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.
Place, publisher, year, edition, pages
Elsevier BV , 2022. Vol. 49, p. 1279-1284
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-360643DOI: 10.1016/B978-0-323-85159-6.50213-XScopus ID: 2-s2.0-85136262348OAI: oai:DiVA.org:kth-360643DiVA, id: diva2:1941394
Conference
14th International Symposium on Process Systems Engineering
Note
Part of ISBN 978-0-443-18726-1
QC 20250303
2025-02-282025-02-282025-03-03Bibliographically approved