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Carleton University

Fall 2000
Dr. Irwin  Pressman


Prerequisites: Business 42.142* and 42.230* and Economics 43.220 or Mathematics 69.266* and 69.267* (with a grade of C- or better in each). It is the responsibility of each student to ensure that he/she has met the prerequisite requirements for the course. Failure to document this requirement will lead to mandatory deregistration from the course. Waiver of any prerequisite requirement can only be granted by the School of Business. Students are urged to IMMEDIATELY contact the School in all cases of doubt, and are reminded that responsibility for this matter rests with the student.

Calendar Description:  Computer-based simulation. Specific topics will include generating random observations, problem formulation, simulation model design, implementation using a computer language, and interpretation of simulation output.


Course Objectives

The objective of this course is to introduce Business students to the essential ideas and tools of computer simulation and to illustrate their applications to the study of business systems. The MATLAB technical computing environment will be used as the basic tool through which the various aspects of simulation modeling are introduced. Our goal is for students to learn how to  model business systems and familiarize themselves with a set of widely used tools. We will study how to develop conceptual models of industrial systems, build computer simulation models from them,  and analyze their simulation results.  However, it is development of critical thinking and analytical skills that are the real goal.

Course Design: The first two weeks of the course will include a crash course in MATLAB.  Do not miss the first lecture because we will spend several hours in a computer lab.You may purchase a copy of the MATLAB PRIMER from the COPY SHOP in LOEB205A for a nominal fee. We will  use MATLAB throughout the term and your skill levels will develop. In the first 2 weeks we will spend part of our time in computer labs. Please attend these lectures.

 I will post the first assignment on the web early so that you can get some feeling as to the direction that the course will take. I expect you to complete assignments on time. Late assignments will be penalized; they are due at 8:30 AM in class on the due date.  I encourage the creation of teams of two but this is NOT required.  You need not have the same partner throughout the course.  We expect that you  will share information about MATLAB with classmates, but it is not appropriate for any student to copy another person's work. Copying of work is a violation of the Senate  Code, and is subject to the sanctions contained therein.
See the relevant sections in the Calendar or:

You are expected to learn to debug your own software. Frequently much is learned by this process. When you identify your mistake you are not likely to repeat it. One possible outcome for slackers is to end up like our friend Walter:

MATLAB will provide a unique opportunity and challenge for students. MATLAB is widely taught in Schools of Engineering.  It has penetrated a few leading Business schools in the U.S.A. (e.g., University of Pennsylvalia,  Wharton Business School course 653: Mathematical Modeling and its Application in Finance, and University of California at Berkeley BA238C: Finance Seminar and E236: Derivatives.)  I have taught MATLAB to a wide range of students in the past, and they have not found it difficult. My goal is that that you will acquire skill in using a  useful, reliable tool set and appreciate the details of the systems involved.

Some Business Schools focus on Spreadsheet systems.  To quote Michael Pidd, a leading authority,  in Computer Simulation for Management Science4'th edition, p. 248:  "Spreadsheet models are ideal for carrying out simple system dynamics simulations,  although they are NOT recommended for large-scale or complicated models.    There is a tendency for spreadsheet models to grow too large and to contain spaghetti-like links between cells. When a spreadsheet model gets into this state it is almost impossible to validate or verify and is probably best scrapped."   This has been my personal experience and is the reason why we will move to a superior set of tools. This may be a competitive advantage for those students considering working for Engineering oriented or consulting firms. There is, however,  a greater demand on the students who will have to acquire some introductory aspects of high-level programming skills in this course.

SOFTWARE: MATLAB is available to all students on the Carleton Unix network on PRINCE.  There will be some stand-alone copies in labs. You can go to the web site for MATHWORKS who are the developers and marketers of MATLAB in case you wish to purchase a copy. Check  regarding special student licensing prices, and concerning STUDENT MATLAB  that is available in the Carleton Bookstore. You are not required to purchase the software. There are manuals in the bookstore

Assignments, class participation,  and presentation of final project 
DUE DATES:  Assignment 1: Sept. 28; Assignment 2: October 19; Assignment 3: November 2
Tests  # 1. Oct. 12 ; # 2. Nov. 9    (15 marks each) 30%
Final take home project:  Due date MONDAY Nov. 27 4-5:30 PM 
BONUS (5% if received Nov. 23 by 3:45PM)
PENALTY (5% if received by 3:45PM Nov. 30, which is the last time projects will be received) 
Total 100%

TEXT: Discrete-Event System Simulation, 3/e
                Jerry Banks,       AutoSimulations
                John S. Carson, AutoSimulations, a Brooks Automation Company
                Barry L. Nelson, Northwestern University
                David M. Nicol, Dartmouth College
Copyright 2001, 594 pp. Prentice Hall. ISBN 0-13-088702-1   Should be in bookstore by Sept. 20.

Topics: Not all topics in each chapter will be covered.

Week 1. Introduction to Simulation.  Introduction to MATLAB. Intercorporate Ownership.
Week 2. MATLAB functions and scripts. Built in tools.  Graphics. Lotteries.
Week 3. Simulation Examples: Chapter 2 . Queueing Systems. Simulation of Inventory Systems.
Week 4. General principles. Other Simulation Software. Chapters 3-4
Weeks 5-6. Statistical Models in Simulation. Distributions. Poisson Process. Queueing Models. Chapters 5-6
Week 6. TEST
Week 7. Random-Number Generation. Monte Carlo methods. Pseudo-Random Numbers.  Chapter 7.
Week 8 . Random-Variate Generation.  Input Modeling. Statistical analysis. Chapter 8-9
Week 9-10  Verification and Validation of Simulation Models. Model Building, Verification, and Validation. Chapter 10.
Week 10. TEST
Week 11. As time permits:  Output Analysis for a Single Model.  Measures of Performance. Steady-State Simulations.Comparison and Evaluation of Alternative System Designs. Optimization. Linear Programming. Introduction to simulation of Manufacturing and Material Handling Systems.  Case Studies. Selected topics. Chapter 11-12
Weeks 12-13. Presentation of projects by the groups (~15-20 minutes each)

Students with Disabilities requiring academic accommodations are to contact a coordinator at the Paul Menton Centre early in the term to complete the necessary letters of accommodations. Then, make an appointment to come and discuss your needs with me at least two weeks prior to the first in-class test. This is to ensure sufficient time to make the necessary accommodation arrangement.

Reference Texts :

Albright, S.C.,  W. L. Winston, and C.  Zappe Data Analysis and Decision Making. Duxbury (1999)
Banks, J. Handbook of Simulation, Wiley Interscience,  John Wiley and Sons (1998).
Clemen, Robert T.  Making  Hard Decisions: An Introduction to Decision Analysis. Duxbury (1996).
Fishman, G. S.  Principles of Discrete Event Simulation. John Wiley and Sons (1978).
Hanselman, D. and B. Littlefield, MASTERING MATLAB 5, Prentice Hall  (1998).  Excellent reference. In bookstore soon.
Khoshnevis, B.  Simulation.  McGraw-Hill, Inc. (1994).
Law, A. M. and W. D. Kelton  Simulation Modelling and Analysis, Second Edition, McGraw-Hill (1991).
Pidd, M.  Computer Simulation in Management Science 4th edition. John Wiley and Sons (1998).
Schriber, T. J.  An Introduction to Simulation Using GPSS/H, John Wiley & Sons (1991).
Thesen, Arne and Travis, L. E. Simulation for Decision Making, West Publishing, St. Paul, (1992).
Vose, D. Quantitative Risk Analysis, John Wiley and Sons (1996).
Winston W.L. Simulation Modeling Using @Risk  Duxbury Press (1996).
Winston W.L.,  and S. C. Albright Practical Management Science, Wadsworth (1997) Discrete Systems

©Irwin Pressman ; School of Mathematics and Statistics, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S& 5B6

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