Description: Simulation methods and algorithms to modeling and analysis of real-world complex stochastic systems. Generating random objects (random variables and stochastic processes, discrete-event systems), input and output analysis, steady-state simulation, variance-reduction methods, rare-event simulation, Markov chain Monte Carlo methods, simulation-based optimization. This course discusses simulation algorithms and their analysis for applications in operations research (service operations, healthcare, queueing, networks, inventory, finance). It is supplemented by practical programming exercises. Cross-list: CAAM 485. Recommended Prerequisite(s): MATH 212, (STAT 310 or STAT 311 or 418), (CAAM 334 or CAAM 335), CAAM 382, MATH 302