Simulation is a widely used methodology in both industry and academia because it is a vital tool for decision making under uncertainty. A simulation model allows the user to test a variety of “what-if” scenarios on a computer and evaluate a variety of outcomes from complex processes before considering implementing any changes to the real system. Areas of application include health care, finance, risk analysis, manufacturing, logistics, call centers, and military.
This course introduces students to discrete-event simulation for modeling complex, dynamic processes. Because queueing often plays a big role in these processes, we will begin with an introduction to queueing theory. We will then learn how to model complex processes with a widely used discrete-event simulation software package.
Instructor Biography – Steven Shechter
Course Outline – Class of 2018 (updated February 15, 2018)
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