/The art of creating a computer model behaving as
a system under perception /
Scope
Introduction, familiarization
and efficient utilization of simulation theory and practices
Syllabus
Introduction
to basic simulation concepts and terminology.
Event-driven
and process-driven simulation. Simulation project cycle.
Queuing
systems. Probabilities and statistics.
Object-oriented
programming. Building reliable models.
Random number
generation. Generation of random variates. Output analysis for terminating and
non-terminating experiments.
Modeling
formalisms – the DEVS formalism.
Real-Time and
Faster-than-Real-Time Simulation. Examples and applications.
MODSIM and
ARENA simulation languages.
Lecture
Schedule
Final
Grade
The course
involves both exams and a group project that must be completed by students.
Group
formation is left to students, provided that each group has up to 3 members.
The final grade is calculated as
follows:
Final Grade
=0.5*Exam_G +0.5*Proj_G
Slides
Recommended
Reading
A.M. Law, W.D. Kelton, Simulation Modeling and Analysis,
McGraw Hill
D. Kelton, Simulation with Arena, McGraw Hill
B. Zeigler, H. Praehofer, T. Kim, Theory of Modeling and
Simulation, Academic Press
P. Fishwick,
Simulation Model Design and Execution, Prentice Hall
Αποτελέσματα Ιουνίου 2003-2004
Simulation Links
The Society for Computer Simulation
International
The ACM Special Interest Group
on Simulation
Paul Fishwick’s work on
Computer Simulation
Systems Modeling Simulation LAB in
KAIST
Bibliography
for Discrete Events Systems Simulation