Author:

Keywords:

Science & Technology, Life Sciences & Biomedicine, Technology, Biotechnology & Applied Microbiology, Engineering, Chemical, Engineering, Multi-objective optimisation, Dynamic optimisation, Bioprocess, NORMAL-BOUNDARY INTERSECTION, NORMAL CONSTRAINT METHOD, REDUCED SQP STRATEGY, MULTICRITERIA OPTIMIZATION, SYSTEMS, Computer Simulation, Models, Biological, Software, 0903 Biomedical Engineering, 0904 Chemical Engineering, 1003 Industrial Biotechnology, Biotechnology, 3106 Industrial biotechnology, 4004 Chemical engineering

Abstract:

The optimal design and operation of dynamic bioprocesses gives in practice often rise to optimisation problems with multiple and conflicting objectives. As a result typically not a single optimal solution but a set of Pareto optimal solutions exist. From this set of Pareto optimal solutions, one has to be chosen by the decision maker. Hence, efficient approaches are required for a fast and accurate generation of the Pareto set such that the decision maker can easily and systematically evaluate optimal alternatives. In the current paper the multi-objective optimisation of several dynamic bioprocess examples is performed using the freely available ACADO Multi-Objective Toolkit (http://www.acadotoolkit.org). This toolkit integrates efficient multiple objective scalarisation strategies (e.g., Normal Boundary Intersection and (Enhanced) Normalised Normal Constraint) with fast deterministic approaches for dynamic optimisation (e.g., single and multiple shooting). It has been found that the toolkit is able to efficiently and accurately produce the Pareto sets for all bioprocess examples. The resulting Pareto sets are added as supplementary material to this paper.