Response surface method combined with data analysis to optimize extraction process problem

Find and develop an appropriate optimization approach is directly associated with the reduction of the time and labor employed in a given chemical process and could be decisive for quality management. In this context, this work presents an approach to implement the Response Surface Method. This technique combines Response Surface Method with Genetic Algorithm and data mining. The main objective is to develop in MATLAB® a method able to optimize the surface function based on three variables using Hybrid Genetic Algorithms combining with Cluster Analysis to reduce the number of experiments and to find the closest value to the optimum within the established restrictions. The results are in accordance with those reported in a previous study. The proposed method has proven to be a promising alternative strategy since the optimal value was achieved without going through derivability unlike conventional methods, and fewer experiments were required to find the optimal solution in comparison to the previous work using the traditional Response Surface Method.
This work has been supported by FCT - Funda¸c~ao para a Ci^encia e Tecnologia within the Project Scope: UIDB/05757/2020.

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