Discrete-event Stochastic Simuliation

Host University

University of Virginia

Semester

Spring 2023

Credits

3

Discipline

Systems Engineering, Operations Research and Engineering Management

Instructor

Brian Park

Course Information

A first graduate course covering the theory and practice of discrete-event stochastic simulation. Coverage includes Monte Carlo methods and spreadsheet applications, generating random numbers and variates, specifying input probability distributions, discrete-event simulation logic and computational issues, review of basic queueing theory, analysis of correlated output sequences, model verification and validation, experiment design and comparison of simulated systems, and simulation optimization. Emphasis includes state-of-the-art simulation programming languages with animation on personal computers. Applications address operations in manufacturing, distribution, transportation, communication, computer, health care, and service systems. Prerequisite: SYS 6005 or equivalent background in probability, statistics, and stochastic processes.