Using a Bipolar Choquet Neural Network to Locate a Retail Store

In this paper, we propose and apply a novel analytical method for solving a class of location problems. The method is based on the use of the bipolar Choquet integral in a neural network for classifying alternative locations. The method is applied to the case study that consists of finding a location for a new store of a major Brazilian retail company. A comparison between the use of the proposed method and the TODIM-FSE method is presented in the paper. The method can also be applied to a situation when one has millions of patterns and new patterns have to be recognized. The paper closes with identifying the proposed method as being efficient and ready to be used with structured and non-structured data systems in order to discover relevant and still unknown information.