Discrete-Event Simulation: A First Course
Discrete-Event Simulation: A First Course
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This paper provides an introduction to simulation fundamentals via the Monte Carlo and next-event approaches to simulation, supported by two representative programs from the software suite written specifically for the Winter Simulation Conference's Simulation 101 workshop. The simulation libraries and functions associated with workshop are written using the R statistical language. R is suitable for an introduction to simulation because of its easy learning curve and its wide range of statistical procedures, built-in functions, and graphics capabilities. This paper begins with general instructions for downloading, compiling, and executing the software. This is followed by explanations of the Monte Carlo and next-event approaches, using two examples: craps() uses Monte Carlo simulation to estimate the probability of winning the dice game Craps, and ssq3() uses a next-event approach to estimate several measures of performance associated with a single-server queue.