# Department of Information and Computing Sciences

## Onderwijs Informatica en Informatiekunde

Vak-informatie Informatica en Informatiekunde

# Simulation

Course code:INFOSIM
Credits:7.5 ECTS
Period:period 3 (week 6 through 16, i.e., 6-2-2012 through 20-4-2012; retake week 22)
Timeslot:B
Participants:up till now 21 subscriptions
Schedule:Official schedule representation can be found in Osiris
Teachers:Dit is een oud rooster!
formgrouptimeweekroomteacher
lecture          Marjan van den Akker

Contents: The course is open for MBI students. MBI students who take the course should have a positive attitude towards quantitative aspects and modelling. The course contains some statistics. Knowledge on this is not required beforehand. MBI students who have completed `Wetenschappelijke onderzoeksmethoden' and/or Advanced Research Methods already have some interesting knowledge. For questions please contact the teacher.

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 building project, it is important to know if the new terminal is indeed sufficient 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 also play a role. However, they occur in combination with continuous simulation models (differential equations) and are outside the scope of the course.

We study the following topics: simulation modelling, validation and verification, input and output analysis, random number generators, queueing theory and inventory theory. Moreover, we consider planning problems with uncertainty. Moreover, we study applications by means of cases, papers and an assignment.

Literature:The basic lectures are based on the book:
Simulation modeling and analysis, A.M. Law, McGraw-Hill Higher Education. ISBN 978-0-07-110336-7 (fourth edition). Also available at the library.
The book is not mandatory but recommended. If you attend the lectures you are able to learn the material from the notes that you take during lectures together with the slides . It might be interesting to obtain the third edition of the book at a reduced price.
Course form:Lectures, workshops, seminar.
Exam form:To pass the course the following is required:
1. Modeling assignment must be completed
2. Simulation assignment: TBD, contributes 30 %
3. Seminar presentation, contributes 25 %
4. Final exam, contributes 45 %, unrounded! grade has to be at least 6.
5. Participation in mandatory sessions.
Minimum effort to qualify for 2nd chance exam:Om aan de aanvullende toets te mogen meedoen moet de oorspronkelijke uitslag minstens 4 zijn.
Description:In the course we try to achieve a mixture of theory and application. The theoretical part of the course consists of lectures and exercises. The application part contains analysis of concrete cases. Moreover, in the assignment students have to perform a simulation study (important part is of course the implementation of a simulation). Finally, there is a seminar part where students present a paper.

Required knowledge are basics of statistics and some modelling experience. The course can be followed by master's students computer science. Because of the relevance of simulation in e.g. logistics the course may also be interesting for MBI students who have affinity with mathematics and computer sciences. Finally, the course can be followed by mathematics students with interest in operations research.

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