SIMULATION – ENM 307
2016 SPRING
Instructor
Office Location
Office Phone
Email
Office Hours
Assistants
Onur Kaya
End 201
6439
onur_kaya@anadolu.edu.tr
Tuesday 14:00-16:00
Leman Esra Dolgun
ledolgun@anadolu.edu.tr
Müge Soyuöz Acar
msoyuoz@anadolu.edu.tr
Course Description
Introduction of simulation models to analyze the behavior of complex stochastic systems. Monte-Carlo
and discrete event simulation. Modeling time and randomness, model validation. Generation of
stochastic inputs, random variate generation. Implementation of models arising from case studies via
simulation languages and software. Output analysis, variance reduction techniques.
Course Objectives
At the end of the course the students will be able to:
1. Model event timing and randomness in a discrete-event dynamic system.
2. Validate and verify simulation models
3. Generate stochastic inputs to simulation models
4. Model and analyze complicated systems using specialized simulation software
5. Statistically analyze simulation output.
Learning Outcomes
At the end of the course the students are expected to:
1.
2.
3.
4.
5.
6.
7.
Define basic elements of simulation and explain the main steps of a simulation study
Generate and understand random variables and random variates
Understand and apply the main principles of Monte-Carlo and discrete event simulation.
Use simulation methodology to model and analyze real discrete dynamic systems
Able to apply input and output analysis in a simulation study
Able to use the software “Arena” to simulate a real life system
Apply the tools and techniques of simulation in a real life team project that involves multiple
scenarios and process improvement
This course contributes to the following Industrial Engineering program learning outcomes
significantly:
1. Gain the ability to identify appropriate models and methods for solving decision problems; analyze
and evaluate alternative or candidate solutions to decision problems
2. Gain the ability to formulate analytical models and develop computer simulations to analyze
systems under uncertainty
3. Gain the ability to analyze and reorganize business and industrial process flows, information flows
and financial flows
Teaching Methods
The course consists of lectures and lab sessions. Lab sessions support lecture material by focusing on
simulation modeling and analysis issues using computer software.
Homework and Review Exercises: The students are encouraged to work on all of the problems that
are given at the end of each chapter. Some of these exercises will be discussed in class and in the lab
sessions.
Lab Sessions: Lab sessions are scheduled primarily to learn ARENA, and discuss some of the
homework and review exercises. There will be some homework assignments related to certain lab
sessions that should be completed after the lab session.
Simulation Project: As a requirement, the students will complete a simulation project in groups of four
or five that will be formed in the first three weeks. The groups will identify a complex system and
analyze it through simulation by using ARENA. They will report their analysis and findings by
submitting a written report and making a presentation.
Lecture notes: Available on the Anadolu University Industrial Engineering web page assigned for this
course.
Course Contents
Session
Number
2
3
2
2
2
2
2
2
2
1
2
2
1
Topics
Basic Simulation Modeling
Modeling Complex Systems
Simulation Software (HW #1)
Review of Basic Probability and Statistics
Midterm 1
Queueing Models
Random Number Generators
Generating Random Variates
Selecting Input Probability Distributions
Building Valid, Credible and Detailed Models
Midterm 2
Output Data Analysis for a Single System
Project presentations
Chapter 1
Chapters 2 -3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Assessment Methods
Type
Description
Midterm 1
Midterm 2
Final Exam
Homework
Project
Total
In-Class Exam
In-Class Exam
In-Class Exam
In-class exercises and assignments
Group project
Final
Grade
%
15
15
40
15
15
100
Sources
Required TextBooks
 J. Banks, J.S. Carson, B.L. Nelson and D.M. Nicol, Discrete-Event System Simulation, 4th
Edition, Prentice Hall, 2005
Recommended Readings
1.
A.M. Law, Simulation Modeling and Analysis, 4th Edition, McGraw-Hill, 2007
2.
W.D. Kelton, R.P. Sadowski and D.A. Sadowski, Simulation with Arena, 2nd Edition, McGrawHill, 2002
3.
S.H. Ross, Simulation, 2nd Edition, Academic Press,1997
Academic Dishonesty
Honesty and trust are important to all of us as individuals. Students and faculty adhere to the following
principles of academic honesty at Anadolu University:
1.
Individual accountability for all individual work, written or oral. Copying from others or providing
answers or information, written or oral, to others is cheating.
2.
Providing proper acknowledgement of original author. Copying from another student's paper
or from another text without written acknowledgement is plagiarism.
3.
Authorized teamwork. Unauthorized help from another person or having someone else write
one's paper or assignment is collusion.
Cheating, plagiarism, and collusion are serious offences resulting in an F grade and disciplinary
action.