NCKU IIM – Introduction to Stochastic Simulation
Fall 2010
Contact Information
Instructor:
蔡青志
Office: 61309
Email: sctsai@mail.ncku.edu.tw
Office Phone: 06-2757575-53135
Teaching Assistants
鄭雅心
Office: 61114
Times and Locations
 Lectures are Tuesday 15:10 – 17:00 and Wednesday 16:10 – 17:00, 61208
 Professor’s Office Hours: Thur. 16:00-17:00, or by appointment
 TA’s Office Hours: Monday 19:00 – 21:00.
Textbook
th
A. M. Law . 2007. Simulation Modeling and Analysis, 4 Edition, McGraw-Hill.
Course Description
An introduction to discrete-event simulation for graduate students. The course covers
simulation modeling and programming in general-purpose languages (specifically C and
VBA) and (briefly) in specialized simulation environments (Arena). Proper design and
analysis of the simulation experiment is emphasized. Applications are drawn from
manufacturing and service systems.
The course prepares students to solve problems using simulation, and to employ
simulation in their research.
Pre-requisites
You should be familiar with basic concepts and techniques in Probability and Statistics (a
good supplemental reference for this would be "Introduction to Probability Models" by
S.M. Ross).
Programming can be done in any language on any computer system. Possibilities include
Arena/SIMAN, Visual Basic, Fortran, Matlab, Maple, Java, C and C++. Class examples
will be coded in VBA/Excel and students are welcome to use this code for their
assignments.
Online teaching system
Lecture ppt files, handouts, homework assignments, data sets, announcements, etc. will
be posted on the following website regularly:
http://aacsb.management.ncku.edu.tw/
Grading
The course grade will be determined by:
 Class participation and other in-class assignments (10%)
 Homework Assignments (25%)
 A midterm exam (30%)
 A cumulative final exam (35%)
Course Policies
Homework: I anticipate there being 8 or 9 homework assignments or roughly every two
weeks. For these assignments, you are encouraged to discuss the problems with your
colleagues, the instructor, or the TA. However you MUST do and hand in your own
work (this applies to both hand-written and computer work). Violation of these rules
constitutes academic misconduct and will be treated accordingly. In order to receive full
credit on the problems you must show your supporting work or attach your computer
programming session. Late turned-in homework will not be accepted.
Exams: Exams will be closed-book, though an 8.5 x 11 cheat sheet (both sides) will be
allowed. No communication is allowed on exams.
Tentative Course Schedule
Week
1
2
3
4-5
6
7
8
9
10
11-12
13
14-15
16-17
18
Topic
D-E Simulation basics and Modeling D-E systems
Programming simulations
Simulation using Simlib
Input modeling
Random-number generation
Random-variate generation
Midterm Exam
Mathematics for simulation
Output analysis for terminating system
Output analysis for steady state simulation
Comparison via simulation
Ranking and selection procedures
Variance reduction techniques
Final Exam
Book
Ch. 1
n/a
Ch. 2
Ch. 6
Ch. 7
Ch. 8
n/a
Ch. 4
Ch. 9
Ch. 9
Ch. 10
Ch. 10
Ch. 11
n/a

Grading percentage for multiple assessment (see the table below):
Percentag
e
25
30
35
10
Item
Hw Assignment
Midterm
Final exam
Participation
IT
10
AACSB at IIM Criteria
OC
PS
CI
15
10
10
15
10
10
VP
10
10
AACSB = The Association to Advance Collegiate Schools of Business
IIM = Industrial and Information Management
IT = Information Technology
Proficiency of using as much IT advantages as possible, such as using the
Simulation software ARENA to solve problems encountered in the industry context..
OC = Oral Communication
Examination of the breadth, the depth, and the structure of the speaking content,
including skills of using non-language expressions, different communication tools
and taking questions.
PS = Problem Solving
Demonstrate exceptional ability in identifying and diagnosing problems encountered
in this context.
CI = Creativity and Innovation
Ideas presented with originality, transparent to solution finding and relevance to the
subject. Degree of getting analysis errors will also be examined.
VP = Values and Professionalism
Being aware of rules, policies and norms used in the statistics arena for display.