A COMBINATION OF NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHMS FOR SOLVING THE OPTIMIZATION PROBLEMS IN PHARMACEUTICS

Abstract

In the pharmaceutical market, all products have a life cycle and out-of-date products should be improved or innovated by new ones. For this reason, design and optimization of formulation are the regular demands. Traditional methods of design and optimization - such as statistics, simplex, ... - have only used for simple and linear data. In the event that data is complicated and non-linear, these methods are not suitably. This paper presents a solution for optimizing formulation and process of production in pharmaceutics by combining of AI technics: neural networks, fuzzy logic and genetic algorithms. This solution helps pharmacist save a lot of time and labor because of its accuracy and processing speed.