Suppose a large airport considers an extension of its terminal to be able to cope with the increasing number of passengers. Before investing a lot of money in a builiding project, it is important to know if the new terminal is indeed suuficient to handle the increased number of passengers. Or to find out, what is the maximum number of passengers in the new situation. A simulation study is very useful tool to obtain an answer to this type of questions.
Simulation is the imitation of systems or processes in the computer to be able to obtain information about their perfomance. Because of the increasing power of computers, it has become an important tool for decision support. It is frequently applied in the area of transportation and logistics, but also for wheather forecast and climate studies and for design of e.g. airplanes and bridges.
A simulation study involves a number of steps: first a problem description and modelling, then implementation, after that experiments have to be conducted and finally the results have to be analysed. In the course, we study discrete-event simulation which means that the state of the system changes at discrete moments in time (step by step). Uncertainties are included in the model by means of stochastic variables. We focus on applications in transportation and logistics. These are modelled as discrete systems. In applications like robotica and aerodynamics, discrete-event simulation models are also important, however, they occur in combination with continuous simulation models (differential equations).
We study the following topics: simulation modelling, validation and verification, input and output analysis, random number generators, and queueing theory. Moreover, we study applications by means of cases, papers and assignments.