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Historically, discrete-event process simulation was first and most widely used in manufacturing contexts. As the technology has gradually matured and knowledge of its benefits has become more widely known, simulation usage has spread to warehouse design and operation, health-care delivery, retail customer service, and (as in this paper), the transport of people and/or goods.

This project simulated the Blue Bus system of the University of Michigan. We analyzed the waiting time of passengers at each stop and the utilization of buses under two strategies; one is based on the schedule, the other is adding eight buses of Bursley-Baits during peak time besides the scheduled shifts which is practical Blue Bus running strategy. Under the two strategies, we analyzed the different scenarios that number of passengers increases by some times. We compared these scenarios and found the practical strategy is more robust when there is a sharp increase of passengers.