Simulation and Modeling

What you’ll study

Systems — the system environment and system components. System models and simulation — types of model and simulation: discrete and continuous, static and dynamic, deterministic and stochastic. Discrete event-driven simulation — components and organization, the event-scheduling and process-interaction approaches, event lists and list processing; the basics of parallel and distributed simulation. Simulation languages and packages — GPSS, the SSF API for Java and C++, Arena, Extend and SIMUL8. Probability and statistical concepts in simulation — random variables and their distributions, stochastic processes, estimation, hypothesis tests and confidence intervals. Queuing models — queuing systems, behaviour and disciplines, arrival and service-time distributions, Little's formula and the analysis of queuing networks. Random-number and random-variate generation and testing; input modelling with and without data; the verification and validation of simulation models; output-data analysis; and the simulation of computer systems and networks.