Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 41, Issue 5, Pages 2186-2195Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2013.09.017
Keywords
Fed-batch fermentation; Differential Evolution; Evolutionary algorithms; Particle Swarm Optimization; Feeding trajectory optimization
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Funding
- ERDF - European Regional Development Fund
- National Funds through the FCT (Portuguese Foundation for Science and Technology) [FCOMP-01-0124-FEDER-015079, PEst-OE/ES/UI0752/2011]
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The optimization of the feeding trajectories in fed-batch fermentation processes is a complex problem that has gained attention given its significant economical impact. A number of bio-inspired algorithms have approached this task with considerable success, but systematic and statistically significant comparisons of the different alternatives are still lacking. In this paper, the performance of different metaheuristics, such as Evolutionary Algorithms (EAs), Differential Evolution (DE) and Particle Swarm Optimization (PSO) is compared, resorting to several case studies taken from literature and conducting a thorough statistical validation of the results. DE obtains the best overall performance, showing a consistent ability to find good solutions and presenting a good convergence speed, with the DE/rand variants being the ones with the best performance. A freely available computational application, OptFerm, is described that provides an interface allowing users to apply the proposed methods to their own models and data. (C) 2013 Elsevier Ltd. All rights reserved.
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