Optimal service channel reconfiguration based on multi-agent simulation

Solving the problem of long queues becomes increasingly urgent in many on-site service outlets. For example, in a bank branch or a government agency, customers may have to wait for a very long time to be served. How to optimally reconfigure the capability of service channels in such outlets is a key for the service providers to improve efficiency and quality of service. In this paper, we propose a method to optimally configure service channels at a given service outlet. We integrate customer experience metrics with cost and profit into a unified objective function for optimization. Multi-agent simulation technique is employed to model the stochastic service processes and customer behavior, and to evaluate the objective function in optimizing service channel capacity. Some real-life data collected from bank branches provide significant empirical support to the method and demonstrate that the presented method is both effective and efficient.