Research On Satisfactory Optimization Method Of Glutamic Acid Fermentation Process

This paper studies chiefly make satisfactory optimization method applying to the optimization of operating variables of fermentation process. Due to the large quantity of complex elements in the practical situation, it is difficult for us to find an accurate math model to describe the corresponding cases, or it is not worth achieving the optimal solution than the cost, and indeed may be there is no optimal solution in the traditional concept. In this case, a popular strategy, satisfactory optimization method, is chosen.Firstly, summarizes the new technique of the optimization, analyzes the limitation of the optimization, reviews the study of satisfactory theory, research objective and research methods. Provides the definition of satisfactory solution and satisfactory degree, and the form of satisfactory degree that frequently used. Introduces the apply of satisfactory theory in different fields, makes comparative analysis between satisfactory theory and optimal theory.Based on the satisfactory theory, mainly discuss the satisfactory optimization method, provide a procedure to solve satisfactory optimization problems. Through the analysis of traditional method on multi-objective optimization, provides a solution of multi-objective satisfactory optimization. Analyzes the feature of satisfactory optimization and genetic algorithm, provides a method of combine satisfactory optimization with genetic algorithm to solve satisfactory problems.Taken the fermentation process of glutamic acid as example, based its feature and production data, a neural network model is established for predicting some important state variables. Using this model, we can predict the tendency of product concentration, biomass concentration, substrate concentration under given conditions.Based on the established neural network predictive model and genetic algorithm technique, optimize concentration in the glutamic acid and conversion rate, the optimal value of operation variables are determined. Combine with satisfactory optimization theory, the multi-objective satisfactory optimization model of glutamic acid fermentation process is established, the satisfactory degree function of each objective is determined, genetic algorithm is used to achieve that two objective optimized at the same time. Simulation results show the effectiveness of the method.