An Interaction-Oriented Model of Customer Behavior for the Simulation of Supermarkets

Since several years, great distribution firms implement more and more complex layout and shelf allocation strategies, so as to force empirical know-how to combine with Artificial Intelligence tools. Thus simulation has become an essential tool for designing efficient article layouts. Mathematical models based on statistical observations have been replaced by agent-based models. In this paper we argue that the modelling of individual behaviors of customers in a supermarket must be done through interaction-oriented approaches, in order to allow large-scale simulations and flexible models. Our model, based on our IODA methodology, is part of a ``Serious Game'' dedicated to vendor training. It takes into account the diversity of customer preferencies, the location of articles, and the side-effects of customer moves, so as to measure the consequence of management choices on the global outcomes of the supermarket.