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Recently the effort of retailers improving the efficiency of store operations by using the information technology (IT) is increasing. Among them, the analysis of the shoppers` flow in retail stores is one of the critical tasks since it is an essential part in optimizing store layout and item grouping, and in developing the customized services specialized to shoppers` classification. Agent-Based Modeling and Simulation (ABMS) is one of the most promising methods which support analyzing the shoppers` flow. In this paper, we suggested a shopper`s behavior model and developed an agent-based simulator for optimizing the operations of retail stores. In order to model the shoppers` behavior, we analyzed the behavioral characteristics of shoppers based on their shopping lists, suggesting BDI-based agent models of the shoppers` behavior. The shopping agent model were suggested, which has an additional mental state, the shopper`s behavioral characteristic, as well as the original mental states of the BDI theory which has beliefs, desires and Intentions. The result of this study can be used in as a preliminary study for modeling and simulation of retail stores congestion and in the end the optimization of item grouping and store layout.

Development of an Agent-based Simulator for Shopping Path Analysis in Retail Stores