MBA 617.01
MANAGEMENT SCIENCE
FALL 2009 SCHEDULE: Thursdays, 8/27/09 to 10/8/09, 6:30-9:20 p.m., 204 Bryan
DR. RICHARD EHRHARDT Office: 480 Bryan
Office phone: 334-4986
Office hours: Mon, Tues & Thurs: 11:00-12:00 p.m.,
Tues & Thurs: 5:30-6:00 p.m.
or by appointment.
E-mail address: r_ehrhardt@uncg.edu
Inclement weather: call 334-5000 after 3:30 pm.
PRE/COREQUISITES MBA 600 (prerequisite), and MBA605, 607 and 610 (corequisite).
TEXTBOOK Albright, Winston & Zappe. Data Analysis & Decision Making with
Microsoft Excel. Thomson/South-Western. 2006. (ISBN 0-324-40082-9)
The 3rd edition, revised for Excel 2007 is preferred, but the version you
purchased for MBA600 & 610 will be fine.
INTRODUCTION
Management science is a scientific approach to decision making which is appropriate
when the important aspects of the decision making environment can be quantified. The
basic idea behind the approach is to construct a mathematical model of a management
situation which shows how outcomes depend upon decisions. Then mathematical
problems can be solved to identify the best decision making alternatives and/or assess the
risks involved.
Management science is a rather new field of study. Although there are a few examples of
mathematical decision making models that date back to the early part of this century,
military applications during World War II gave birth to management science as a field of
study in its own right. The methods that were developed were so successful that industry
rapidly adopted and extended them after the war. Since the early 1950s, management
science has grown into an established discipline, supporting decisions in diverse
applications as illustrated by the following questions.
Which factories should supply which warehouses?
Which bonds should be selected to form an investment portfolio?
How many teller lines should a bank operate?
Where should a firm locate its distribution center?
How large a plant should be built to manufacture a new product?
How much of each product should be made in each of the next 3 months?
How should the firm allocate its budget among various types of advertising?
How risky is the plan for retirement investing?
When should short-term loans be planned for the year’s cash flow needs?
What range of profits might we expect from a new product introduction?
Fall 2009 MBA617.01 page 2
COURSE LEARNING OBJECTIVES
• To develop a disciplined, objective approach to decision making.
• To improve communication skills.
• To improve spreadsheet skills and learn spreadsheet tools for analyzing decision making
problems.
• To develop an understanding of the basic ideas and common models of management
science.
SPECIFIC LEARNING GOALS
Upon completing the course, you should be able to:
1. Use principles of professional spreadsheet design to construct effective models of
decision making situations.
2. Use the Excel Solver tool to find optimal solutions to decision making models.
3. Conduct sensitivity analyses to show how optimal decisions change when input
information is changed.
4. Use Excel to analyze models for planning product mixes, aggregate production over time,
logistics, blending and financial decisions.
5. Discuss different notions of optimality when decisions have uncertain outcomes.
6. Describe the riskiness of a plan using quantitative measures.
7. Construct Excel simulation models to assess the risks of decision making in uncertain
environments.
8. Use simulation models to analyze the returns and risks of decisions in operations
management and financial planning contexts.
COURSE POLICIES
1. Course Format. This course will meet for 7 weeks of instruction, with some time devoted
to lecture and discussion, and some time to computing exercises. If you are absolutely
unable to attend a class, be sure to arrange ahead of time with the instructor and a
classmate to get notes about the material covered and details of assigned problem sets.
2. Computer Files. Files for this course can be found on the CD provided with the text and
at the course Blackboard site. You should download all the files and save them in their
folders (Assignments, Spreadsheet Techniques, Optimization, Decision Analysis and
Simulation) on your laptop. Then you will have all of them immediately available in
class, regardless of the state of wireless access to our network.
Fall 2009 MBA617.01 page 3
3. Problem Sets. Two Problem Sets will be assigned and graded. Each Problem Set will be
composed with a different partner. The details of each assignment will be provided in
class. In each case, you are to submit Excel workbooks with a separate worksheet for
each part of the assignment. Send your file to the Digital Drop Box of the Blackboard site
(Tools/Digital Drop Box/Send). If the Blackboard site is unavailable, then the file may be
sent via electronic mail ( r_ehrhardt@uncg.edu ). Assignments are due on the dates listed
on pages 5 and 6. More guidance on the desired format is given on page 7.
4. Exam Policy. The exam will take an entire class period and will be closed-book, with the
following exceptions: (1) you will be allowed to refer to notes on one 8½×11 sheet of
paper during the exam; and (2) you will have your laptop computer at your disposal. You
may use any files and features available on your laptop provided that you do not
communicate with anyone during the exam.
5. Grading Policy. Your course average will be computed using a weight of 30% for
Problem Set 1 and 35% each for Problem Set 2 and the final Exam. You may increase
your course grade above your course average through good class participation.
6. UNCG Academic Integrity Policy. You are expected to be familiar with and abide by the
UNCG Academic Integrity Policy. The Policy may be found at:
http://academicintegrity.uncg.edu/complete/
Although you are encouraged to discuss assignments with classmates, you are not to
share details of your work. Specifically, you are not to share computer files or printed
output from your computer analysis. Prohibited actions also include working together
side-by-side on separate computers. Violations of the Code will result in penalties
ranging from an F on the assignment to an F in the course.
7. Bryan School Faculty Student Guidelines. The Bryan School faculty has approved a set
of guidelines for the conduct of classes. They can be found at:
http://www.uncg.edu/bae/faculty_student_guidelines_sp07.pdf
Fall 2009 MBA617.01 page 4
TENTATIVE CLASS SCHEDULE: OVERVIEW
Note: Page numbers for the revised 3rd edition are in parentheses below.
August 27: First Class Meeting
Topics
Course Overview
Modeling & Spreadsheets: quick overview
Spreadsheet design for decision making models (Agriculture example)
Optimization Modeling
Linear programming models
Product mix models
Spreadsheet analysis: the Solver tool
Sensitivity analysis reports and the SolverTable Add-in
Assignment models (See the document in the Optimization folder. )
Hands-on session
Modify the product mix model (handout)
Prior to class
Create a folder named MBA617 within “My Documents” in your computer, and then create
subfolders named CaseFiles, ExampleFiles and ProblemFiles within the MBA617 folder.
Create subfolders named DataOnly and Finished within the ExampleFiles folder. Put the
Student CD that comes with the text in your CD drive and copy all the files from Chapters
14, 15,16 and 17 into the appropriate folders that you have just created.
Read this syllabus, Chapter 14 pp. 779-814 (789-824), and the Assignment problem
document (Optimization folder).
September 3: Second Class Meeting
Topics
Linear Optimization Applications
Blending
Finding the least expensive mixture of ingredients to create a product
Logistics models
Transporting and distributing goods and services efficiently
Aggregate Planning models
Planning manufacturing capacity, production and inventory over time
Hands-on session
Rolling-schedule aggregate planning (handout)
Prior to class
Read Chapter 15 pp. 837-839 (847-849), 846-865 (856-875), 870-875 (880-885).
Fall 2009 MBA617.01 page 5
September 10: Third Class Meeting
Topics
Linear Optimization Applications
Financial models
Planning cash flows over time
Integer-valued modeling techniques
Integer-valued and binary decision variables
Hands-on session
Midwest Electric plant selecton (handout)
Prior to class
Read Chapter 15 pp. 879-901 (889-911).
September 17: Fourth Class Meeting (Problem Set 1 due, 6:30pm)
Topics
Decision Analysis
Payoff tables
Organizing unpredictable decision outcomes scenario by scenario
Optimality criteria
Different ways of assessing risk and concluding what’s best
Simulation
Pseudorandom numbers
Making Excel compute values that appear to vary randomly
Hands-on session
Investment example (Excel file)
Prior to class
Read Chapter 7 pp. 305-319 (315-329) and Chapter 16 pp. 935-946 (945-956).
September 24: Fifth Class Meeting
Topics
Spreadsheet simulation modeling
Simulation with built-in Excel tools
Simple simulation modeling
Introduction to @RISK
Using @RISK to specify random inputs, generate replications and analyze output
statistics
Hands-on session
Walton Bookstore variants
Prior to class
Read Chapter 16 pp. 954-981 (964-991).
Fall 2009 MBA617.01 page 6
October 1: Sixth Class Meeting
Topics
Simulation modeling examples, selected from the following topics.
Operations-related models
Planning product warranties; coping with uncertain production yield
Financial models
New product introduction; cash flow planning; IPO pricing
Prior to class
Read Chapter 17 pp. 1004-1027 (1014-1037).
October 8: Final Exam, 6:30pm to 9:20pm
October 13: Problem Set 2 due, 3:30pm (Tuesday)
Fall 2009 MBA617.01 page 7
PROBLEM SETS: FORM AND CONTENT
Two Problem will be submitted for grading by the due dates listed on pages 5 and 6. In
each case, Excel workbooks will be transmitted to the instructor with the analysis of each
problem or project part placed on a separate worksheet. Please send your file to the Digital
Drop Box of the Blackboard site (Tools/Digital Drop Box/Send). If the Blackboard site is
unavailable, then the file may be sent via electronic mail ( r_ehrhardt@uncg.edu ). You
may be permitted to submit an assignment up to one week late if special circumstances
arise. If so, a penalty of one letter grade will be assessed, and no other late submissions will
be permitted.
Your worksheets should be organized and annotated so that they readily communicate your
ideas and the results of your analysis. Remember when composing your worksheets that the
point of the exercise is to demonstrate to your instructor that you understand the principles
and techniques being studied. Your grade will be based upon (1) how well you conduct
your analysis and (2) how professionally you present your results and communicate your
ideas.
The analysis of each problem or project part should begin with a very brief overview of the
essential elements of the model. This should not be a restatement of the problem or project,
but rather a summary that casts the problem in terms that reveal its logical structure. The
quantitative analysis should be sufficiently annotated so as to clearly communicate
methods. Finally, the conclusions of the analysis should be explicitly stated. Be careful to
briefly state the implications of your analysis and to answer any questions that were asked
in the statement of the problem or project part.
BIOGRAPHY
Rich Ehrhardt is from New York City, and began his professional life in physics and
engineering. He earned a BS in physics at The Cooper Union, in New York City, and an
MS in physics at the University of Massachusetts at Amherst. He then began five years on
the technical staff of the U. S. Atomic Energy Commission, during which he spent a year at
the University of California at Berkeley earning an MS in nuclear engineering, and a year
at Argonne National Laboratory performing safety systems research. His responsibilities at
U.S.A.E.C. headquarters in Washington, DC were in the area of civilian electrical power
generation, managing research and development contracts in advanced reactor systems
design and nuclear reactor safety.
He returned to graduate studies in 1973, earning a Ph.D. in administrative sciences at Yale
University in 1976. He was a member of the faculty of UNCCH, in the Department of
Operations Research and in the School of Business, prior to joining the Bryan School
faculty in 1982. His research interests are in stochastic models of operations research,
materials management, and production control systems. He has consulted on materials
management and project management issues with a number of firms and has lectured to
executive groups. Professor Ehrhardt is a member of the Institute for Operations Research
and the Management Sciences, the International Society for Inventory Research, and the
Operations Management Society.