Date of Award
Master of Science in Operations Research
Department of Operational Sciences
Mark A. Gallagher, PhD
This research compares simulations to Dynamic Bayesian Networks in analyzing situations. The research applies models that have known output mean and variance. Queueing systems have theoretical values of the steady-state mean and variance for the number of entities in the system. Monte Carlo simulation development is broken down into two separate approaches: discrete-event simulation and time-oriented simulation. The discrete-event simulation uses pseudo-random numbers to schedule and trigger future events (i.e. customer arrivals and services) and is based on the generated objects.The time-oriented simulation utilizes fixed-width time intervals and updates the system state according to a stochastic process for the set of events occurring during each time period. The accuracy of each approach in estimated by a comparison to the theoretical mean, variance, and probability values.
DTIC Accession Number
Salazar, Aaron J., "Analysis with Dynamic Bayesian Networks Compared to Simulation" (2020). Theses and Dissertations. 3605.