Simulation

1.5 units

This course covers the two key types of simulation models of uncertain events: Monte Carlo simulation and Discrete Event Simulation. The conceptual difference between these two simulation methodologies is in their treatment of time. Discrete Event Simulation is used to model dynamic systems where events occur at specified, random, times. In Monte Carlo simulation, the timing of events is typically inconsequential. Upon successful completion of this course, students will demonstrate competency in formulating and analyzing models under uncertainty using both Excel and state-of-the-art simulation software. They will become proficient with software tools like Arena for Discrete Event Simulation and Crystal Ball for Monte Carlo simulation. The course emphasizes proficiency in using software tools to analyze models rather than theory.