Modeling Operational Demand for Canada's Future Naval Fleet: A Case Study on Maintaining Expected Frequencies of Military Vignettes

The Royal Canadian Navy is currently undertaking a fleet mix study to determine the optimal composition of its fleet to meet future operational requirements. The operational demand is modeled by generating possible future timelines of vignettes that can occur concurrently using a Monte Carlo discrete event simulation model. In this paper, we examine two aspects related to modeling operational demand stochastically: the number of replications required to ensure that the input frequencies of the vignettes correspond to a certain level of accuracy in the output frequencies from the simulation; and how the application of concurrency constraints to individual vignettes may lower the output frequencies if events are scheduled purely at random. We propose a modified scheduling algorithm that better maintains the input frequencies. Both aspects need to be taken into consideration to ensure that the modeled operational demands are representative of possible and probable futures for the Navy.