Simulation Methods
Objectives:
In the end of this course, the students should be able to
• Effectively develop their computing skills on simulation.
• Apply the appropriate mathematical and statistical methods to design models and process simulations.
• Use the most sophisticated tools for simulating processes from a variety of scientific areas.
Skills:
Programming
Prerequisites:
Statistics and Basic Knowledge on Programming
Content:
Systems study, continuous systems (construction of analytical models and sensitivity analysis), discrete systems (activities and events), Petri nets, process modeling with Petri nets, Simulation Timing Mechanisms, Simulation Languages (GPSS, MATLAB, SIMULINK) and development of simulation models for a variety of scientific fields, Randomness controls, Analysis of simulation results, deterministic systems simulation, queue models.
Textbooks:
Manos Roumeliotis and Stavros I. Souravlas «Simulation Techniques-Theory and Applications», 2nd Edition, 2015, Tziolas Publications.
As supportive material, the following textbooks could be used:
1. D. Maki, M. Thompson, Mathematical Modeling and Computer Simulation,
Brooks/Cole, 2006.
2. G. S. Fishman, Discrete-Event Simulation, Springer, 2001.
Moreover, any paper or reference found from any electronic source.
Assessment:
During the course, the students will work on two small projects (10% of the final grade for each one) and on a big project assigned to them in the middle of the semester (30% of the final grade). The remaining 50% of the final grade is taken from the final exam.
