Ghost simulation model for discrete event systems, an application to a local bus service

In this paper we present a simulation model for large networks that increases the efficiency compared to a discrete event simulation model. These networks have two different time scales: a fast one and a slow one. The main idea is to replace some of the faster point processes by a “fluid” (called the ghost processes) thus accelerating the execution of the simulation. Using local modularity for the code, there is no need to keep a list of events. Clocks are not necessarily synchronized. When a local clock advances due to a slower event, retrospective calculations recover the fine detail lost in the fluid model. Mathematically, the model is a special case of the Filtered Monte Carlo method. Efficiency improvement results not only from the speed of execution, but also from variance reduction. We provide proofs of unbiasedness. Throughout the paper we use a case scenario of an airport car park.