Geodesic
Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms
Serdica Journal of Computing, Tome 4 (2010) no. 1, pp. 11-18.

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Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.
Keywords: Genetic Algorithms, Parameter Identification, Fed-Batch Cultivation of S. Cerevisiae 
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Angelova, Maria; Tzonkov, Stoyan; Pencheva, Tania. Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms. Serdica Journal of Computing, Tome 4 (2010) no. 1, pp. 11-18. http://geodesic.mathdoc.fr/item/SJC_2010_4_1_a1/