ОПТИМІЗАЦІЯ ЦІНОУТВОРЕННЯ НА ОСНОВІ МОДЕЛЕЙ ІНТЕЛЕКТУАЛЬНОГО АНАЛІЗУ ДАНИХ

The purpose of this paper is to develop and implement an approach for solving the optimization problem in the retailers goods market and different consumers groups based on a hybrid model of intelligent data analysis. It is revealed that for each consumer type product information array formed consisting of the factors values that affect the company revenue. An example of the optimal prices hybrid model synthesis in the product (beer) market and grocery stores network were considered. Solving the problem of optimizing product prices by consumer groups was implemented in two stages: first constructed interpolation function of consumer demand each group, and then solve the problem of optimizing implicitly given function. Demand function obtained by artificial neural networks.