A Hybrid Genetic Algorithm for Parameter Identification of Bioprocess Models
In this paper a hybrid scheme using GA and SQP method is introduced. In the hybrid GA-SQP the role of the GA is to explore the search place in order to either isolate the most promising region of the search space. The role of the SQP is to exploit the information gathered by the GA. To demonstrate the usefulness of the presented approach, two cases for parameter identification of different complexity are considered. The hybrid scheme is applied for modeling of E. coli MC4110 fed-batch cultivation process. The results show that the GA-SQP takes the advantages of both GA’s global search ability and SQP’s local search ability, hence enhances the overall search ability and computational efficiency.
KeywordsGenetic Algorithm Local Search Sequential Quadratic Programming Hybrid Scheme Hybrid Genetic Algorithm
Unable to display preview. Download preview PDF.
- 5.Gill, P.E., Wong, E.: Sequential Quadratic Programming Methods, UCSD Department of Mathematics, Technical Report NA-10-03 (2010)Google Scholar
- 6.Levisauskas, D., Galvanauskas, V., Henrich, S., Wilhelm, K., Volk, N., Lubbert, A.: Model-based Optimization of Viral Capsid Protein Production in Fed-batch Culture of Recombinant Escherichia coli. Biopr. & Biosys. Eng. 25, 255–262 (2003)Google Scholar
- 9.Paplinski, J.P.: The Genetic Algorithm with Simplex Crossover for Identification of Time Delays. Intelligent Information Systems, 337–346 (2010)Google Scholar
- 10.Roeva, O.: Improvement of Genetic Algorithm Performance for Identification of Cultivation Process Models, Advanced Topics on Evolutionary Computing. Artificial Intelligence Series-WSEAS, pp. 34–39 (2008)Google Scholar
- 12.Roeva, O., Pencheva, T., Hitzmann, B., Tzonkov, S.: A Genetic Algorithms Based Approach for Identification of Escherichia coli Fed-batch Fermentation. Int. J. Bioautomation 1, 30–41 (2004)Google Scholar