Iqra University
Karachi
Management Science
Course Study Guide
Academic Year 2013
Fall Semester
¶
MBAProgramme
Department of Management Science
Management Science 2013
Course Study Guide for Management Science
cont’d
1. INTRODUCTION
This course is an introduction to the basic theory underlying Management Science and
Operations Research. It focuses on linear programming, the fundamental concepts, and
algorithms. Applications drawn from different functional areas of business will also be
presented. In particular, the course will cover a variety of applications of management science
in the areas of finance, marketing, and production such as capital budgeting, optimal sales
allocation, and scheduling and distribution. Special cases of linear programming problems,
such as the transportation problem and assignment problems will also be studied
Learning Goals

To introduce students to the subject of Management Science, and a variety of
management science models, methods and computational procedures that are helpful
in solving management problems in Finance, PoM., Accounting, M.I.S., Marketing,
Operational Research, Actuarial Science, etc..Emphasis is placed on models and their
solutions.

To give students a good foundation in basic problem solving as a preparation for
upper level quantitative courses (Finance, Production/ Operations Management,
Accounting, M.I.S., Marketing, Operational Research, Actuarial Science, etc.).

To develop in students an appreciation of the management science approach to
problem formulation and solution, so important in the modern business and industrial
world with the increased use of computers..
PREREQUISITES:
It is assumed that students taking this course have completed the Business Mathematics
course and also have a good foundation in basic statistics and probability theory as covered in
the statistical inference course. Although some review of elementary concepts and
terminology is provided in the textbook, it is not intended to replace a complete course, but
rather to refresh your memory. While a high degree of mathematical skill is not necessary in
an “applied” course such as this, there are certain insights into the course that are gained
through the mathematics involved.
REQUIRED TEXT:
Anderson, Sweeney, Williams, Camm and Martin, An Introduction to Management Science:
Quantitative Approaches to Decision Making, 13th Edition, © 2011 South Western
Educational Publishing (an imprint of Cengage Learning) ISBN-10: 1439043272, ISBN-13:
9781439043271.
(It is alright if you have bought the 12th Edition of this textbook, which has the author
“Camm” missing in the author roll. You will however need to reconcile the Self test
Exercises, end-of-chapter Cases and problems with the 13th edition as needed. I will be
using the 13th edition in class.)
COURSE FACILITATOR: Imtiaz Arif arif.i@iuk.edu.pk
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Course Study Guide for Management Science
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There is a lot of reading to do to support the broad scope of this course. A selection of key
readings is given for each session. You will be given additional readings to follow up the
sessions. Ask your course facilitator for advice on further reading on a topic which interests
you.
2. ASSESSMENT
The assessment for the course is based on quiz, assignment and two exams, mid-term and
final exam
The mid-term and the final exam will cover both the theory and application of topics covered
in classes and the readings. The mid-term test and final examination are closed-book and
closed-notes. Both midterm and final will consist of multiple choice and short essay/problem
type questions. The date for the final exam will be posted by the University later in the
semester.
Assignment schedule
The assignment is due no later than 06:30 p.m. on mentioned day.
3. STUDYING PRINCIPLES AND PRACTICE
This course brings together a range of topics and ideas which need to be related to your
experience and context of work. There are many potentially relevant ideas, so you should
expect to find that you receive a lot of information and that there is not time to go into all of it
in depth. You will have to be selective, as the facilitator is in what they present, and what we
work on in class. However, you should endeavour to cover a range of topics and not focus
simply on one area of personal interest.
To get the most out of classes you will need to do preparatory reading. This may include a
handout given in advance, and a journal article which you will find in the fileserver library; in
addition other readings are suggested, but you are not expected to complete all of these. You
will have to select what you can find or what interests you. However it is strongly
recommended that you do at least some reading around all or most of the topics covered.
In class you will be expected to take part in discussions. You should come to class with
questions and comments about the preparatory readings. The aim of these activities is to help
you explore your professional experience against the background of the ideas.
1. TIMETABLE OF THE CLASSES
Week
Topics
Introduction to Decision Theory
1.
Week1
• Problem Solving and Decision Making
• Introduction to Quantitative Analysis
• Models of Cost, Revenue and Profit
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Course Study Guide for Management Science
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Introduction to Linear Programming
2.
Week 2
• Maximization and Minimization Problems
• Graphical Solution Procedure
• Formulating Spreadsheet Models
Linear Programming: Sensitivity Analysis
3.
Week 3
• Sensitivity Analysis
• More Than Two Decision Variables
Linear Programming Applications
• Marketing Applications
4.
Week 4
• Financial Applications
• Production Management Applications
• Blending Problems
• Simplex Method
Transportation, Assignment and
Transshipment Problems
5.
Week 5
• The Transportation Problem
• The Assignment Problem
• The Transshipment Problem
Network Models
6.
Week 6
• Shortest-Route Problem
• Minimal Spanning Tree Problem
• Maximum Flow Problem
Project Scheduling: PERT/CPM
7.
Week 7
8.
Week 8
• Project Scheduling with known Activity Time
• Project Scheduling with Uncertain Activity
Times
Mid-Term Examination (No Class)
Project Scheduling: PERT/CPM
9.
Week 9
• Project Scheduling with Uncertain Activity
Times
• Considering Time-Cost Trade Offs
10.
Week 10
Contd.
Waiting Line Models
• Structure of a Waiting Line System
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Course Study Guide for Management Science
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• Waiting Line Models


Single-Channel, Multiple-Channel
Economic Analysis of Waiting Lines
Simulation
11.
Week 11
• Risk Analysis
• Inventory Simulation
• Waiting Line Simulation
Decision analysis
• Structuring the Decision Problem
12.
Week 12
• Decision Making with and without Probabilities
• Decision Analysis with Sample Information
• Computing Branch Probabilities
Multi-criteria Decisions
13.
Week 13
• Goal Programming
• Scoring Model
Multi-criteria Decisions
14.
Week 14
Contd.
• Analytic Hierarchy Pro (Tulsian & Pandaey,
2004)ess
• Using AHP to Develop an Overall Priority
Ranking
Forecasting
• Component of Time Series
15.
Week 15
• Smoothing Methods
• Trend Projection
• Trend and Seasonal Components.
Markov Processes
16.
Week 16
• Market Share Analysis
• Account Receivable Analysis
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Course Study Guide for Management Science
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OUTLINE OF SESSIONS AND PREPARATORY READINGS
Week 1
Introduction to Decision Theory
Key readings
 (2009). An Introduction to Decision Theory. In D. R. Anderson, D. J. Sweeney, & T.
A. Williams, An Introduction to Management Science (pp. 3-18).
Week 2
Introduction to Linear Programming
Key reading
 (2009). An Introduction to Linear Programming. In D. R. Anderson, D. J. Sweeney,
& T. A. Williams, An Introduction to Management Science (pp. 31-60).
 (2004). Linear Programming. In P. C. Tulsian, & V. Pandaey, Quantitative
Techniques (pp. 1.1-1.57).
Week 3
Linear Programming: Sensitivity Analysis
Key reading
 (2009). Linear Programming Sensitivity Analysis. In D. R. Anderson, D. J. Sweeney, &
T. A. Williams, An Introduction to Management Science (pp. 96-122).
Week 4
Linear Programming Applications
Key reading
 (2009). Linear Programming Applications. In D. R. Anderson, D. J. Sweeney, & T.
A. Williams, An Introduction to Management Science (pp. 153-168).
Week 5
Transportation, Assignment and Transshipment Problems
Key reading
 (2009). Transportation, Assignment and Transshipment Problems. In D. R.
Anderson, D. J. Sweeney, & T. A. Williams, An Introduction to Management Science
(pp. 306-350).
 (2004). Assignment Problem. In P. C. Tulsian, & V. Pandaey, Quantitative
Techniques (pp. 4.1-4.43).
 (2004). Transportation Problem. In P. C. Tulsian, & V. Pandaey, Quantitative
Techniques (pp. 5.1-5.24).
Week 6
Network Models
Key reading
 (2009). Network Models. In D. R. Anderson, D. J. Sweeney, & T. A. Williams, An
Introduction to Management Science (pp. 428-446).
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Course Study Guide for Management Science
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Week 7
Project Scheduling: PERT/CPM
Key reading
 (2009). Project Scheduling: PERT/CPM. In D. R. Anderson, D. J. Sweeney, & T. A.
Williams, An Introduction to Management Science (pp. 306-350).
 (2004). PERT. In P. C. Tulsian, & V. Pandaey, Quantitative Techniques (pp. 7.1-7.4).
Week 9
Project Scheduling: PERT/CPM
Contd.
Key reading
 (2009). Project Scheduling: PERT/CPM. In D. R. Anderson, D. J. Sweeney, & T. A.
Williams, An Introduction to Management Science (pp. 306-350).
 2004). Cretical Path Method (CPM). In P. C. Tulsian, & V. Pandaey, Quantitative
Techniques (pp. 6.1-6.70)
 (2004). Crashing, Resource Allocation and Smoothing. In P. C. Tulsian, & V.
Pandaey, Quantitative Techniques (pp. 8.1-8.41).
Week 10
Waiting Line Models
Key reading
 (2009). Waiting Line Models. In D. R. Anderson, D. J. Sweeney, & T. A. Williams,
An Introduction to Management Science (pp. 306-350).
 (2004). Queueing Theory. In P. C. Tulsian, & V. Pandaey, Quantitative Techniques
(pp. 9.1-9.8).
Week 11
Simulation
Key reading
 (2009). Simulation. In D. R. Anderson, D. J. Sweeney, & T. A. Williams, An
Introduction to Management Science (pp. 585-619).
 (2004). Simulation. In P. C. Tulsian, & V. Pandaey, Quantitative Techniques (pp. 11.111.8).
Week 12
Decision Analysis
Key reading
 (2009). Decision Analysis. In D. R. Anderson, D. J. Sweeney, & T. A. Williams, An
Introduction to Management Science (pp. 306-350).
 (2004). Decision Tree. In P. C. Tulsian, & V. Pandaey, Quantitative Techniques (pp.
12.1-12.2).
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Course Study Guide for Management Science
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Week 13 & 14
Multicriteria Decisions
Key reading
 (2009). Multicriteria Decisions. In D. R. Anderson, D. J. Sweeney, & T. A. Williams,
An Introduction to Management Science (pp. 712-742).
Further reading
 Analytical Hierarchical Process http://www.youtube.com/watch?v=18GWVtVAAzs
Week 15
Forecasting
Key reading
 (2009). Forecasting. In D. R. Anderson, D. J. Sweeney, & T. A. Williams, An
Introduction to Management Science (pp. 758-784).
Further reading
 Forecasting http://www.youtube.com/watch?v=DVEbZ__FNRg&feature=related
 Time series Analysis http://www.youtube.com/watch?v=cC2kE2RcN68
Week 16
Markov Processes
Key reading
 (2009). Markov Process. In D. R. Anderson, D. J. Sweeney, & T. A. Williams, An
Introduction to Management Science (pp. 808-821).
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