The Lee Kong Chian School of Business
Academic Year 2014 /15
Term 2
OPIM 101 MANAGEMENT SCIENCE
Instructor
Title
Tel
Email
Office
: Pascale Crama
: Assistant Professor of Operations Management
: 6828 0330
: pcrama@smu.edu.sg
: LKCSB #4031
COURSE DESCRIPTION
The objective of this course is to introduce students to management science, which is the application of the
scientific method to managerial and personal decision-making. The quantitative analysis approach consists of
defining a problem, developing a model, acquiring data, developing a solution, testing the solution, analyzing
results and implementing results. Selected quantitative analysis tools will be introduced in the course which
include linear and integer programming, decision analysis, and project scheduling.
LEARNING OBJECTIVES
By the end of this course, students will be able to:
- Analyze the business or personal problem situation and structure it
- Formulate a quantitative model to represent the problem situation using the techniques learned
- Solve the problem using the techniques learned
- Interpret the results and perform what-if analyses to gain insights
- Explain the usefulness and the limitations of the modeling approach to solving decision problems
PRE-REQUISITE/ CO-REQUISITE/ MUTUALLY EXCLUSIVE COURSE(S)
Please refer to the Course Catalogue on OASIS for the most updated list of pre-requisites / co-requisites for
this particular course.
Do note that if this course has a co-requisite, it means that the course has to be taken together with another
course. Dropping one course during BOSS bidding would result in both courses being dropped at the same
time.
ASSESSMENT METHOD
Homework Assignments & Cases: 20%
Class Participation: 10%
Midterm Exam: 35% (midterm exam scheduled in class in week 7)
Final Exam: 35% (final exam to be scheduled by the Office of the Registrar).
ACADEMIC INTEGRITY
All acts of academic dishonesty (including, but not limited to, plagiarism, cheating, fabrication, facilitation of acts
of academic dishonesty by others, unauthorized possession of exam questions, or tampering with the academic
work of other students) are serious offences.
All work (whether oral or written) submitted for purposes of assessment must be the student’s own work.
Penalties for violation of the policy range from zero marks for the component assessment to expulsion,
depending on the nature of the offence.
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When in doubt, students should consult the course instructor. Details on the SMU Code of Academic
Integrity may be accessed at http://www.smuscd.org/resources.html.
INSTRUCTIONAL METHODS AND EXPECTATIONS
Lectures, in-class tutorials and discussions.
The slides alone are not sufficient study material. The slides are meant to be complemented by notes taken
during the lecture or by additional reading in the recommended textbook if not attending classes. The class
will also provide you with hands-on experience of solving problems.
HOMEWORK SUBMISSION
The homework is always due at 5pm the day before the next class. Submission can be made in hardcopy in the
pigeon hole on the fourth floor of LKCSB. No softcopies will be accepted.
RECOMMENDED TEXT AND READINGS
Ragsdale. Managerial Decision Modeling, Revised Edition. Thomson South-Western, 2008.
Render, Stair and Hanna. Quantitative Analysis for Management, Revised Edition. Pearson, 2006.
CLASS SCHEDULE
Week
No.
1
Topic
Readings
Introduction to Management Science and Quantitative Analysis
Ragsdale, Ch. 1, 2
2
Introduction to LP, Graphical Solution
Ragsdale, Ch. 2
3
Solving LP in Excel, Sensitivity Analysis
Ragsdale, Ch. 3 – 4
4
Model formulation
Ragsdale, Ch. 3
5
Binary Variables and Logical Constraints
Ragsdale, Ch. 6
6
Network Models and Midterm Review
Ragsdale, Ch. 5
7
MIDTERM EXAM
8
Mid-term Break
9
Probability Concepts and Applications
Ragsdale, Ch. 15
10
Decision Analysis, Part I: Decision Rules, Sensitivity Analysis,
Decision Trees
Ragsdale, Ch. 15
11
Decision Analysis, Part II: Value of Information, Risk Profiles
Marginal Analysis
Ragsdale, Ch. 15
12
Project Management, Part I: Deterministic Analysis
Ragsdale, Ch. 14
13
Project Management, Part II: Probabilistic Analysis
Ragsdale, Ch. 14
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