This simulation course is based on Kleijnen, J.P.C. (2008), Design and Analysis of Simulation Experiments, Springer.
Lectures are meant to informally explain Kleijnen (2008). Class attendance is not mandatory. Lectures will also cover Questions & Answers about the Homework Assignments that are handed out, every few weeks; see the 2008 Assignments (updated November 19, 2008).
Mandatory material for the exam (if any; see below): Kleijnen (2008) plus documents -- if any -- handed out during these lectures.
There will be no exam except for those students who do not solve the Homework Assignments well enough. More precisely: The average grade of the Homework Assignments determines the final grade for the assignments. Students must form teams of two members to solve these assignments; team members get the same grade (unless they request different grades, but it is a "zero sum game"; i.e. the sum of two times the original grade is reallocated to the two members). If a student team delivers an assignment after the deadline, then they get a grade of zero; i.e., I do not accept late deliveries. If the average grade for the assignment is below a six, then the team must take an exam, which determines 50% of their final grade (the other 50% is determined by the assignments).
If Ph.D. students also take this course, then different rules may apply after contacting their supervisors.
Prerequisite knowledge: basic simulation, mathematical statistics, and operations research; see
Law, A.M. (2007), Simulation modeling and analysis, fourth edition, McGraw-Hill Book Company, New York, chapters 1, 4, 6, 9, 10, 11 (= pp. 1-90, 214-242, 275-388, 485-618 = approximately 350 pages)
Course objective: Students should acquire a sound theoretical knowledge of the statistical design and analysis of experiments with simulation models.
Contents: Simulation uses a computer to model the behavior of a dynamic system (for example, a company, a supply chain), so that the performance of that system can be quantified. That simulated performance can be used to optimize the system or to do sensitivity ('what-if') and uncertainty ('risk') analyses. Simulation models are often part of Decision Support Systems (DSS), Entreprise Resource Planning (ERP), Supply Chain Management (SCM), Business Process Redesign (BPR), etc. Simulation is an Operations Research method that is very often applied in practice, so many case studies will be briefly discussed in the lectures.
Compulsory Reading: Those chapters of the following book that will be discussed during the nine class meetings; i.e., Chapters 1 through 3 plus a selection (decided during the course) from Chapters 4 through 6.
1. Kleijnen, J.P.C. (2008), Design and Analysis of Simulation Experiments, Springer
2. During the course, PowerPoint slides are made available; those slides are mandatory exam material. These slides summarize Kleijnen (2008).
The 2008 PowerPoint (PPT) slides and the corresponding PDF files are available for the next chapters of Kleijnen (2008):
[September 2015: the PPT/PDF files mentioned on this Subpage are not yet available.]
Also see the next slides with very brief summaries of Chapters 5 and 6:
and see the Kriging and Screening slides on Seminar Subpage.
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PDF files of PowerPoint slides are available for all chapters of Law & Kelton (2000); these slides were used in September-November 2005 at Tilburg University, and may be useful for obtaining the prerequisite knowledge.
Chapter 2 Kelton's comments on Chapter 2
Chapter 4 quantile estimation in Arena
Chapter 10 Arena program comparing two M/M/1 systems
Chapter 11 Arena program with CRN for M/M/n systems
Chapter 12 Analysis of replicated design Arena assignment
The following notes supplement the Arena book by Kelton et. al (1998):
1. "Arena's steady-state analysis applied to M/M/1"
2. "Arena's pseudorandom streams applied to M/M/1"
2005 simulation exam at Technical University Eindhoven (there was no 2006 exam):
Simulation exams at Tilburg University:
Exams August 2004 - August 2002
Exams January 2002 - August 2001
Recommended (not mandatory) literature:
Banks, J., J.S. Carson, B.L. Nelson, and D.M. Nicol (2005), Discrete-event system simulation, fourth edition. Prentice-Hall, Upper Saddle River, New Jersey (USA), approximately 600 pages
This book covers the same material as Law (2007).
Cheng, R.C.H. (1998), Random variate generation. Chapter 5 in Handbook on Simulation, ed. J. Banks, Wiley, New York
L' Ecuyer, P. (1998), Random number generation. Chapter 4 in Handbook on Simulation, ed. J. Banks, Wiley, New York
Also see Subpage Publications