Interactive Evolutionary Computation for Model based Optimization of Batch Fermentation

At the optimization of temperature and feeding profiles of batch processes it is often desirable to consider several objectives and constraints into the optimization problem. During the beer fermentation a temperature profile is applied to drive the process so as to obey to certain constraints. The design of this temperature profile is an optimization problem where the objective is to minimize the operation time and optimize the quality of the beer. Similarly to other practical problems, these objectives and constraints are often non-commensurable and the objective functions are explicitly/mathematically not available. In this paper, Interactive Evolutionary Computation (IEC) is used to effectively handle such optimization problems. IEC is an evolutionary algorithm whose fitness function is provided by human users. The proposed approach has been implemented in MATLAB and applied to design temperature profile for beer fermentation process. The results show that IEC is an efficient and comfortable method to incorporate the priori knowledge of the user into the model based optimization of batch processes. A detailed description of the proposed approach helps the construction of the algorithms; still easier, the developed EAsy-IEC Toolbox and the beer fermentation model written can be downloaded from the website of the authors: http://www.fmt.vein.hu/softcomp/EAsy