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Discrete-event simulation is one of the most important techniques available for studying complex stochastic systems. In this paper we review the principal methods available for analyzing both the transient and steady-state simulation problems in sequential and parallel computing environments. Next we discuss several of the variance reduction methods designed to make simulations run more efficiently. Finally, a short discussion is given of the methods available to study optimization using simulation.