A Combined Algorithm for Multi-objective Fuzzy Optimization of Whey Fermentation

M. Petrov and T. Ilkova

Abstract
In this paper, multi-objective fuzzy optimization is applied to finding an optimal policy of a fed-batch fermentation process for lactose oxidation from a natural substratum by a strain Kluyveromyces marxianus var. lactis MC 5. The optimal policy consisted of feed flow rate, feed concentration of the substrate and initial concentration of the substrate. The multi-objective problem corresponds to the process productiveness, and the cost of the substrate. A simple combined algorithm guidelines the finding of a satisfactory solution to the general multi-objective optimization problem. The combined algorithm includes a method for random search for finding an initial point and a method based on fuzzy sets theory, combined in order to find the best solution of the optimization problem. The obtained optimal control results have shown an increase of process productiveness and a decrease of the remaining objective functions.

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Keywords
Multi-objective fuzzy optimization, fuzzy sets theory, random search with back step, combined algorithm, whey fermentation