CULTIVATION PROCESS OPTIMIZATION BASED ON GENETIC ALGORITHMS
Olympia N. Roeva, Tanya V. Trenkova
Pages: 121-136
Published: 1 Jan 2010
Views: 173
Downloads: 15
Abstract: Various approaches have been used to describe nonlinear behaviour of bioprocesses. Some of them are directly based on the divide-and-conquer strategy. These, so-called local approaches can often give a simplified and transparent nonlinear model or optimal control representation. The cultivation process can be divided into several functional states (FS) by considering the cell metabolism in more detail. The maintenance of the appropriate FS could ensure an optimal run of the process. In this paper a feed rate profile that leads to defined FS is synthesized. For the profile synthesis a genetic algorithm (GA) is developed and applied using four objective functions. Nowadays the most common direct methods used for global optimization are GA. The GA are directed random search techniques, based on the mechanisms of natural selection and genetics, which can find a global optimal solution in complex multidimensional search spaces. The obtained results have presented the ability of GA to generate an optimal feed rate profile based on defined rules. The GA generates feed rate profile, that for a short time leads the process to the FS, determined as optimal, and maintains this state during the process. As a result a high final biomass concentration is achieved under optimal conditions for amount and assimilation of the substrate.
Keywords: cultivation process, functional states, feed rate profile, genetic algorithm, optimal control
Cite this article: Olympia N. Roeva, Tanya V. Trenkova. CULTIVATION PROCESS OPTIMIZATION BASED ON GENETIC ALGORITHMS. Journal of International Scientific Publications: Materials, Methods & Technologies 4, 121-136 (2010). https://www.scientific-publications.net/en/article/1003414/
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