COURSE INTRODUCTION AND APPLICATION INFORMATION
Code
Course Name
Decision Theory
Pre-requisites
ENM 442
:
Course Language
:
Course
Type(CompulsoryElective)
:
Course Level
:
Course Coordinator
Course Lecturers
Course Assistants
:
:
:
:
Course Objective
:
Course Learning
Outcomes
:
8
3
ECTS
Credit
4.5
Probability
English
Elective
Undergaduate
Refail Kasımbeyli
Refail Kasımbeyli
Emine Akyol
The objectives of this course are to familiarize students with the introductory knowledge
on modelling, analysis and solution approaches for decision making situations under
uncertainty, under risk, under certainty and in situations with multiple criteria.
The students:
will be able to analyze problems faced in certainty, uncertainty and risk
environments,
will be able to develop decision trees to find rational solutions for problems
under uncertainty and risk environments,
will be able to calculate the value of information,
will be able to use fundamentals of the utility theory,
will be able to analyze different solution aspects of multicriteria problems,
will be able to use scalarization methods for solving multicriteria problems
will be able to use fundamental approaches of goal programming.
This course is one of the basic sections of Operations Research, which studies a
rational process for selecting the best of several alternatives. The “goodness” of a
selected alternative depends on the quality of the data used in describing the decision
situation. From this standpoint, a decision-making process can fall into one of three
categories.
1.
Course Content
(Short definition)
Semester
Lesson
(hour/week)
Application
(hour/week)
Laboratory
(hour/week)
2.
3.
4.
Decision-making under uncertainty in which the data cannot be assigned
relative weights that represent their degree of relevance in the decision
process.
Decision-making under risk in which the data can be described by probability
distributions.
Decision-making under certainty in which the data are known deterministically.
Decision making in multicriteria environment.
The main subjects of the course are the decision situation, decision rule, decision trees,
information and the cost of additional information, utility theory, mult-objective
problems, solution notions for such problems and methods for calculations efficient
solutions for multi-objective problems, goal programming and the methods of analyzing
solutions for goal programming problems.
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
Week
Subjects
1
Introduction to Decision Theory. Decision
Environments. Elementary Decision Analysis.
2
Classification of decision problems. Choosing a
Decision Rule.
3
Decision making under uncertainty.
4
Decision making under risk.
5
Utility theory. Single-attribute utility.
6
Utility functions for non-monetary attributes. The
axioms of utility.
7
Attitudes towards risk.
8
Decision Trees. The use of decision trees in
environments under certainty, under uncertainty and
under risk.
9
Perfect and imperfect information. Expected value of
sampling information.
10
Using additional information.
11
Decision making in multicriteria environment. Order
relations. Various concepts of solutions in multiobjective optimization.
12
Scalarization methods in mult-objective optimization
13
Intoduction to Goal Programming. Linearization of goal
programming problems.
14
Geometrical interpretation of solutions in goal
programming. Examples on Goal Programming
Related Preparation
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 1.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 2.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 2.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 2.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 3.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 3.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 3.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 4.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 4.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 4.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 5.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 5.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 5.
Refail Kasımbeyli, Lecture
Notes on Decision Theory,
Chapter 5.
SOURCES
:
Course Notes
Refail Kasımbeyli, Lecture Notes on Decision Theory, Izmir University of Economics,
2011.
:
1.
Paul Goodwin, George Wright, Decision Analysis for Management Judgment,
Third Edition, John Wiley & Sons, Ltd., 2004, ISBN: 0-470-86108-8.
2.
Robert T. Clemen, Terence Reilly, Making Hard Decisions With Decision Tools,
Duxbury Thomson Learning, 2001; ISBN-13: 978-0-495-01508-6; ISBN-10:
0495-01508-3.
3.
Wayne L. Winston, Operations Research. Applications and Algorithms, Duxbury
Press, Belmont, California, 1994.
4.
Frederick S. Hillier, Gerald J. Lieberman, Introduction to Operations Research,
Ninth Edition, 2010 Mc Graw-Hill, ISBN 978 0-07-337629-5.
Other Sources
5.
Hamdy A. Taha, Operations Research. An Introduction, , Sixth Edition, 1997,
Prentice-Hall, ISBN 0-13-281172-3.
6.
Vira Chankong and Yacov Y. Haimes, Multiobjective Decision Making: Theory
and Methodology, Elsevier Publishing Co., Inc., New York, 1983.
7.
Johannes Jahn, Basic Concepts of Vector Optimization, in T. Gal, T. Hanne, T.
Stewart, Advances in MCDM (Kluwer), 1998.
8.
Howard Raiffa, Decision Analysis, ISBN:0201062909.
Presentation
Exams
EVALUATION SYSTEM
SEMESTER REQUIREMENTS
SAYISI/
NUMBER
KATKI PAYI/
PERCENTAGE
OF GRADE
5
2
10
10
1
1
40
40
100
60
40
100
Attendance
Lab
Application
Field Work
Special Course Internship
Homework Assignments
Quiz
Project
Seminar
Mid-Terms
Final
TOTAL
PERCENTAGE OF SEMESTER WORK
PERCENTAGE OF FİNAL EXAM
TOTAL
COURSE CATEGORY
Course Category
(Only one category will be chosen)
Core Courses
Major area courses
Supportive Courses
Media and management skills courses
Transferable skill courses
X