IFAO-Simo: A spatial-simulation based facility network optimization framework

This paper describes an innovative framework, iFAO-Simo, which integrates optimization, simulation and GIS (geographic information system) techniques to handle complex spatial facility network optimization problems ever challenged from retailing, banking and logistics nowadays. At the top level of iFAO-Simo, an optimization engine serves to generate and test candidate solutions iteratively by use of optimization algorithms such as Tabu Search and Genetic Algorithms. For each scenario given by the candidate solutions, a discrete event simulation engine is triggered to simulate customer and facility behaviors based on a GIS platform to characterize and visualize the spatial, dynamic and indeterministic environments. As the result, the target measures can be easily calculated to evaluate the solution and feedback to the optimization engine. This paper studies a real case of banking branch network optimization problem, and the results show that iFAO-Simo provides a useful way to handle complex spatial optimization problems.