artículo
Hybrid simulation-optimization based approach for the optimal design of single-product biotechnological processes
Fecha
2012Registro en:
10.1016/j.compchemeng.2011.07.013
0098-1354
WOS:000300812600012
Autor
Brunet, Robert
Guillen Gosalbez, Gonzalo
Ricardo Perez Correa, J.
Antonio Caballero, Jose
Jimenez, Laureano
Institución
Resumen
In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer (R) with an external NLP solver implemented in Matlab (R). The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid L-lysine. (C) 2011 Elsevier Ltd. All rights reserved.
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