/The art of creating a computer model behaving as a system under perception /
Introduction, familiarization and efficient utilization of simulation theory and practices
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.
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
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