Process Superstructure Optimization through Discrete Steepest Descent Optimization: a GDP Analysis and Applications in Process Intensification - Bernal, David E.; Ovalle, Daniel; Liñán, David A.; Ricardez-Sandoval, Luis A.; Gómez, Jorge M.; Grossmann, Ignacio E. (Computer Aided Chemical Engineering, 2022)
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.