UNIVERSITI UTARA MALAYSIA
COLLEGE OF ARTS AND SCIENCES
COURSE CODE : SQQP 5023
COURSE NAME : DECISION ANALYSIS
1.0
COURSE SYNOPSIS
Mathematical tools have been applied for thousands of years; however, the formal
study and application of quantitative techniques to practical decision making is
largely a product of the twentieth century. Decision analysis refers to a body of
techniques that allows a decision-maker to evaluate uncertainty, risk, and multiple
objectives decision problems. Among the topics that will be covered in this course
are decision theory, forecasting, linear programming, transportation and
assignment models, waiting line analysis, simulation, network flow models and
project management.
2.0
LEARNING OUTCOMES
2.1
2.2
2.3
3.0
To develop a conceptual understanding of commonly applied management
science techniques in the context of business problems.
To apply the selected management science techniques in the context of
business problems.
To discuss the assumptions, the advantages and the limitations of each of
the management science techniques in solving business related problems.
COURSE CONTENTS
DATE
TOPIC
HOURS
Introduction
 Approaches in Quantitative Modeling
 A Historical Overview
 The Process of Quantitative Modeling
Review of Probability Concepts
 Fundamental Concepts
01/09/2012
 Bayes’s Theorem
 Random Variables & Probability Distribution
Fundamentals Of Decision Theory
 An Overview of the Decision Theory
 Types of Decision Making Situations
 Decision Making Under Risk
 Decision Making Under Uncertainty
7
3 hrs
DATE
TOPIC
HOURS
Decision Trees And Utility Theory
 Decision Trees
 Probability Values Estimated by Bayesian
Analysis
 Utility Theory
02/09/2012
Forecasting
 Selecting a Forecasting Method
 Approaches to Forecasting
 Qualitative Approaches to Forecasting
o Delphi Method
o Panel Consensus
 Statistical Forecasting Methods
o Time Series
o Regression Methods
o Econometric Models
Linear programming
 Formulating linear programming problems
 The Graphical Method
o Maximization Problem
29/09/2012
o Minimization Problem
 Post Optimality Analysis
 Linear Programming – Applications
Transportation and Assignment Problems
 Formulating the Transportation Problem
 Solving the Transportation Problem
30/09/2012
o Stepping Stone Algorithm
o MODI Method
 The Assignment Problem
Waiting Lines Analysis
 The Basic Structure of Queuing
 The Queuing Models
○ Single-Channel Queue
○ Multiple-Channel Queue
13/10/2012
 Applications of Queuing Models
Simulation
 Intoduction to simulation modeling
 Output analysis

 Verification and validation
3 hrs
7
7
7
7
DATE
TOPIC
HOURS
Network Flow Models
 The Shortest Route Problem
 The Minimum Spanning – Tree Problem
The Maximum – Flow Problem
14/10/2012 Project Management
 Program Evaluation and Review Technique
(PERT)
 PERT / Cost
 Critical Path Methods (CPM)
 CPM / Cost
21/10/2012 FINAL EXAM
4.0
7
2.5
REFERENCES
Render, B., Stair Jr, R. M., & Hanna, M. E. (2012). Quantitative analysis for
management (11th Ed.). Prentice Hall.
Taylor, W.B. (2010). Introduction to management science (10th Ed.). New Jersey:
Prentice Hall.
Albright, S. C. & Winston, W. L. (2007). Management science modeling, Quebec:
Thomson Higher Education.
Anderson, D. R., Sweeney, D. J., Williams, T. A., & Martin, K. (2008). An
introduction to management science: Quantitative approaches to decision
making (12th Ed.). Ohio: South-Western College Publishing.
Hillier, F. S. & Hillier, M. S. (2003). Introduction to management science: A
modeling and case studies approach with spreadsheets. New York:
McGraw Hill.
Lawrence Jr, J. A. & Pasternack, B. A. (2002). Applied management science:
Modeling, spreadsheet analysis, and communication for decision making,
New York: John Wiley & Sons Inc.
5.0
TEACHING METHOD
This class will be taught through 42 hours of lectures and discussions.
6.0
ASSESSMENT
Assessment will be made by examinations, assignments and project work.
Coursework
70%
Final
30%