Constructing a Customer's Satisfactory Evaluator System Using GA-Based Fuzzy Artificial Neural Networks

In this paper, an important principle of economical survival in the business area has been studied. It has been considered by increasing the success rate in selling the products in order to overcome on other competitors. This can be achieved thereafter of taking suitable strategic decisions for the enterprise. It is while; the strategic decision determination is based on the quality analysis of the current organization. The analysis is based on the linguistic values received from the customers where the fuzzy modeling, as one of the possible ways, has been used to process these values. The customer's satisfaction has been considered as a key factor for the analysis based on his/her preference as the scope of the qualification for the organization service. In this paper, a new approach has been proposed to provide the reliability of the strategic decisions for an enterprise. This approach considers fuzzy artificial neural networks based on the genetic algorithm to construct a customer's satisfactory evaluator system in order to approximate the quality of the service. The proposed system is able to predict the quality values of the possible strategies according to customer's preference. Finally, the ability of this system in recognizing the customer's preference has been tested using some new assumed services.