A STORE LAYOUT PLANNING METHOD FOR UNDERGROUND SHOPPING STREETS SIMULATION USING HUMAN FLOW DATA AND GENETIC ALGORITHM

Abstract

Many underground shopping streets are located around terminal stations and the majority of passersby use them as a route for transferring between transportation systems, etc. Therefore, placing stores that attract the interest of passersby along their route will lead to an increase in the number of customers. However, it is difficult to determine the layout of stores in an underground shopping streets because people who have various purposes pass through and there are many stores. In this study, simulation and optimization methods are combined to determine the store layout. An agent simulation is constructed using the measured human flow data and used to evaluate the fitness of the optimization method. Computer experiments will be conducted to verify the effectiveness of the proposed method.