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Computer Simulation Techniques:
The definitive introduction!
by
Computer Science Department
NC State University
Raleigh, NC
Harry Perros
All rights reserved 2003
TO THE READER…
This book is available for free download from my web site:
http://www.csc.ncsu.edu/faculty/perros//hp.html
Self-study: You can use this book to learn the basic simulation techniques by yourself!
At the end of Chapter 1, you will find three examples. Select one of them and do the
corresponding computer assignment given at the end of the Chapter. Then, after you read
each new Chapter, do all the problems at the end of the Chapter and also do the computer
assignment that corresponds to your problem, By the time you reach the end of the book,
you will have developed a very sophisticated simulation model !
You can use any high-level programming language you like.
I am not responsible for any errors in the book, and if you do find any, I would appreciate
it if you could let me know (hp@csc.ncsu.edu).
Please remember that it is illegal to reproduce parts of this book or all of the book
in other publications without my consent.
Enjoy!
Harry Perros, June, 2003
TABLE OF CONTENTS
Chapter 1.
Introduction,
1
1.1. The OR approach,
1
1.2. Building a simulation model,
2
1.3. Basic simulation methodology: Examples,
5
1.3.1 The machine interference model,
5
1.3.2 A token-based local area network,
10
1.3.3 A two-stage manufacturing system,
16
Problems,
18
Computer assignments,
19
Generating pseudo-random numbers,
21
2.1. Introduction,
21
2.2. Pseudo-random numbers,
22
2.3. Congruential methods for generating pseudo-random numbers,
22
2.4. Other pseudo-random number generators,
24
2.4.1 General congruential methods,
24
2.4.2 Composite generators,
25
2.4.3 Tausworthe generators,
26
2.5. Statistical tests of pseudo-random number generators,
26
2.5.1 Runs test,
27
2.5.2 Chi-square test for goodness of fit,
28
Problems,
28
Computer assignments,
29
Generating stochastic variates,
31
3.1. Introduction,
31
3.2. The inverse transformation method,
31
3.3. Sampling from continuous probability distribution, 33
Chapter 2.
Chapter 3.

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