16 Simulation and Review
When a system is too complicated for formulas, with several kinds of customers, priorities, breakdowns, finite buffers and non-exponential times, it can still be studied by imitating it on a computer: generate random arrivals, service times and failures, follow the system through time, and average what happens. This is simulation. It answers almost any question about almost any model, but only approximately, with a statistical error that must be estimated, and only for the scenarios that are run. This last section explains how simulation works, how to measure its accuracy and reduce its error, and then reviews the course.
16.1 The Monte Carlo method
16.2 Random numbers and random variates
16.3 Discrete-event simulation
16.4 Variance reduction
16.5 Simulation in software
16.6 Review of the course
16.7 Practice Problems
16.2 Random numbers and random variates
16.3 Discrete-event simulation
16.4 Variance reduction
16.5 Simulation in software
16.6 Review of the course
16.7 Practice Problems
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