MGM3163 (Quantitative Techniques), Semester 2 2013-2014, PAGE 1
MGM3163 (QUANTITATIVE TECHNIQUE) Syllabus
Semester 2 2013-2014
Instructor: Mrs Manisah Othman
Office: Block A 231
Phone: 7694
e-mail: manisah@upm.edu.my; manisahoth@gmail.com
Office Hours: Mondays - Thursday 9:00 - 12:00, 2.00 - 5:00
Fridays
9:00 - 11:45, 3:00 - 5:00
Text: Taylor, B. (2013).
Introduction to Management Science.
(11th ed.). New Jersey: Prentice Hall.
Course Description: This course discusses the quantitative
models as tool for decision makings that will cover issues of
model formulation probability concepts, expected and conditional
value, decision theory, inventory control, linear programming
using simplex method, dual problem and sensitivity analysis,
transpotation model, game theory, queuing theory, simulation and
PERT/CPM
Prerequisite:
MTH 3004.
Course Objectives:
1. Describe the business problem in mathematical models
2. Solve a mathematical model using the appropriate technique.
3. Using a computer package to solve a variety of mathematical
models.
4. Distinguish between different business problems and use
appropriate modeling techniques
Course Outline:
I.
Introduction to Management Science (Chapter 1)
A.
B.
II.
Decision making; discipline of management science
Model building; breakeven analysis
Modeling with Linear Programming (Chapter 2)
A.
B.
Model Formulation
Graphical method (maximization & minimization)
MGM3163 (Quantitative Techniques), Semester 2 2013-2014, PAGE 2
Course Outline (continued)
III. Linear Programming : Sensitivity Analysis (Chapter 3)
A.
B.
Computer Solution
Sensitivity Analysis.
IV.
Linear Programming : Product Mix (Chapter 4)
A. Product Mix Example
B. A Diet Example
C. An Investment Example
D. A Marketing Example
V.
Linear Programming : Transportation Problems (Chapter 6)
A.
B.
C.
VI.
The Transportation Model
The Transshipment Model
The Assignment Model
Network Model (Chapter 7)
A.
B.
C.
Shortest Route Problem
The Minimal Spanning Tree Problem
The Maximal Flow Problem
VII. Managing Projects (Chapter 8)
A. The Element of Project Management
B. CPM/PERT
C. Probabilistic Activity Times
D. Project Crashing
VIII. Decision Making Models (Chapter 12)
A. Components of Decision Making
B. Decision Making Without Probabilities
C. Decision Making With Probabilities
IX.
Waiting Line (Chapter 13)
A. Elements Of Waiting Line Analysis
B. Single Server
X.
Simulation (Chapter 14)
A. The Monte Carlo Process
B. Continuous Probability Distribution
MGM3163 (Quantitative Techniques), Semester 2 2013-2014, PAGE 3
Testing and Grading: Each student's grade will be determined by
the number of points that he/she accumulated during the
semester. There will be total 100 possible points derived from
the following sources: mid-term, homework, tutorial, project and
a final exam. The final exam will cover topics discussed after
the previous test.
The overall grade will be computed as follows
Quizzes (week 4)
Midterm exam ( 20/4/2014)
Final exam
Project
Homework/ Class participation
Tutorial
Total
5%
20% (DKEP 1 , 10 – 12pm)
35%
10%
20%
10%
100%
Attendance: You are expected to be present each class period
except when special hardships occur, e.g. illness. More than 8
hours absences will mean an automatic not allowed to sit for the
final examination.
Homework:
Homework will be assigned at the end of each class
period.
Homework is considered an essential learning tool and
provides excellent preparation for tests. Some assignments will
include use of the computer and will be handed in for a grade.
Project (Individual or Team)
The objective of this project is to develop the skill to
structure a practical problem. The student will identify a
business problem (personal business is also acceptable), and use
one of the methods covered in this course to structure a
spreadsheet that can be used to support decision making to solve
this problem. An example of such a problem could be which health
insurance plan you should choose in light of their premiums and
benefits. Another example could be about optimal financial
portfolio analysis of various investment options. Yet another
example would be to support decisions for how many items to keep
of each SKU in a category in the inventory - when we have an
idea of the demand and substitution patterns for these items. It
is not absolutely necessary to have actual data for the problem,
realistic values for model input parameters can be determined
based on qualitative research results.
MGM3163 (Quantitative Techniques), Semester 2 2013-2014, PAGE 4
Students can discuss their project topic ideas with the
instructor to get feedback. The project teams/ individual
students will prepare a short project proposal identifying the
topic - the decision problem with the objective, decisions to be
made,
and
important
issues
to
be
considered
including
assumptions, constraints, deterministic or probabilistic nature
and the planning horizon, by week 6 and will discuss in class.
The students will present their work in class in the last week
of classes. The final report and the spreadsheet are due in the
finals week. The report should be a maximum of five pages with
the following contents:

definition of the business problem with the key issues and
the key question;

description the spreadsheet model and how it helps answer
the key question;

description of the data needs – essentially the inputs of
the model;

list of model assumptions and an assessment of how
appropriate they are for the business situation, including
the determination of two model parameters for sensitivity
analysis

sensitivity analysis on the two key parameters of the model

recommendation on the key question based on the model
output and sensitivity analysis
The students can choose to do this project as a team of two to
three, or individually.