Welcome to this graduate course on Discrete-Event Simulation, a hybrid
discipline that combines knowledge and techniques from Operations
Research (OR) and Computer Science (CS) (Figure 1). Due to the fast and
continuous improvements in computer hardware and software, Simulation
has become an emergent research area with practical industrial and services
applications. Today, most real-world systems are too complex to be modeled
and studied by using analytical methods. Instead, numerical methods such as
simulation must be employed in order to study the performance of those
systems, to gain insight into their internal behavior and to consider
alternative (“what-if”) scenarios. Applications of Simulations are widely
spread among different knowledge areas, including the performance analysis
of computer and telecommunication systems or the optimization of
manufacturing and logistics processes. This course introduces concepts and
methods for designing, performing and analyzing experiments conducted
using a Simulation approach. Among other concepts, this course discusses the
proper collection and modeling of input data and system randomness,
the generation of random variables to emulate the behavior of the real
system, the verification and validation of models, and the analysis of the
experimental outputs.
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