A first graduate course covering the theory and practice of Monte Carlo and discrete-event simulation.  Coverage includes Monte Carlo methods and spreadsheet applications, generating random numbers and variates, specifying input probability distributions, review of basic queueing theory, discrete-event simulation logic and computational issues, analysis of correlated output sequences, model verification and validation, comparisons based on simulated systems, and simulation optimization.  Emphasis includes state-of-the-art simulation software suites for stochastic simulation.  Applications address operations in manufacturing, health care, distribution, transportation, communication, computer, military, and service systems.