Interactive Multi‐objective Dynamic Optimization of Bioreactors under Parametric Uncertainty. Issue 3 (10th December 2018)

• Record Type: Journal Article
• Authors: Nimmegeers, Philippe; Vallerio, Mattia; Telen, Dries; Van Impe, Jan; Logist, Filip
• Other Names: Asprion Norbert guestEditor.; Eck Bernd guestEditor.
• Is Part Of: Chemie Ingenieur Technik. Volume 91:Issue 3(2019)
• Page Start: 349
• Page End: 362
• Publication Date: 2018-12-10
• Subjects: Multi‐objective optimization -- Robustness -- Sigma point method -- Uncertainty propagation; Chemical engineering -- Patents -- Periodicals; Chemical engineering -- Periodicals; Chemical industry -- Periodicals; Chemistry, Technical -- Periodicals; 660.05
• DOI: 10.1002/cite.201800082
• Languages: English
• ISSNs: 0009-286X

Abstract

Abstract: Model‐based optimization techniques play a key role in achieving a sustainable operation of biochemical processes. Models are an approximation of the real process under study, hence, uncertainty is inherently present and for a sustainable process operation this uncertainty should be accounted for. In practice, optimality with respect to different conflicting objectives is required and multi‐objective optimization is a valuable tool. In this article the sigma point approach is applied to account for parametric uncertainty in the frame of interactive multi‐objective bioprocess optimization. Abstract : In this article a methodology is presented for decision makers to select an optimal operating point from a set of Pareto optimal solutions using an open source software toolkit for interactive multi‐objective dynamic optimization while accounting for parametric uncertainty.