FACULTY OF ENGINEERING
Department of Computer Engineering
IE 342 | Course Introduction and Application Information
Course Name |
Decision Theory
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
IE 342
|
Fall/Spring
|
3
|
0
|
3
|
5
|
Prerequisites |
|
|||||||
Course Language |
English
|
|||||||
Course Type |
Elective
|
|||||||
Course Level |
First Cycle
|
|||||||
Mode of Delivery | - | |||||||
Teaching Methods and Techniques of the Course | Lecture / Presentation | |||||||
Course Coordinator | ||||||||
Course Lecturer(s) | ||||||||
Assistant(s) | - |
Course Objectives | 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. |
Learning Outcomes |
The students who succeeded in this course;
|
Course Description | 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 decisionmaking process can fall into one of three categories. 1. Decisionmaking under uncertainty in which the data cannot be assigned relative weights that represent their degree of relevance in the decision process. 2. Decisionmaking under risk in which the data can be described by probability distributions. 3. Decisionmaking under certainty in which the data are known deterministically. 4. 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, multiobjective problems, solution notions for such problems and methods for calculations efficient solutions for multiobjective problems, goal programming and the methods of analyzing solutions for goal programming problems. |
|
Core Courses | |
Major Area Courses | ||
Supportive Courses | ||
Media and Management Skills Courses | ||
Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
Week | Subjects | Related Preparation |
1 | Introduction to the Course. Introduction to Decision Theory. Behavioral decision analysis. | |
2 | Decision making under certainty. Decision making under uncertainty. Decision making under risk | |
3 | Utility Theory. Single attribute utility. Probability-equivalence approach. | |
4 | Interpreting utility functions. Utility functions for nonmonetary attributes. | |
5 | The axioms of utility. Certainty equivalence approach. | |
6 | Attitudes towards risk. Risk premium. Decreasing and constant risk aversion. | |
7 | Midterm | |
8 | Value of information. | |
9 | Expected value of perfect information. | |
10 | Expected value of sample information. | |
11 | Multicriteria Decision Making. Goal Programming. | |
12 | Analytic Hierarchy Process. | |
13 | Multiattribute Utility Theory | |
14 | Outranking relations. | |
15 | Review | |
16 | Review |
Course Notes/Textbooks | Lecture Notes |
Suggested Readings/Materials | 1. Robert T. Clemen, Terence Reilly, Making Hard Decisions With Decision Tools, Duxbury Thomson Learning, 2001; ISBN13: 9780495015086; ISBN10: 0495015083. 2. Wayne L. Winston, Operations Research. Applications and Algorithms, Duxbury Press, Belmont, California, 1994. |
EVALUATION SYSTEM
Semester Activities | Number | Weigthing |
Participation |
1
|
5
|
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques |
1
|
30
|
Portfolio | ||
Homework / Assignments | ||
Presentation / Jury | ||
Project | ||
Seminar / Workshop | ||
Oral Exams | ||
Midterm |
1
|
30
|
Final Exam |
1
|
35
|
Total |
Weighting of Semester Activities on the Final Grade |
3
|
65
|
Weighting of End-of-Semester Activities on the Final Grade |
1
|
35
|
Total |
ECTS / WORKLOAD TABLE
Semester Activities | Number | Duration (Hours) | Workload |
---|---|---|---|
Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
3
|
48
|
Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
0
|
|
Study Hours Out of Class |
14
|
3
|
42
|
Field Work |
0
|
||
Quizzes / Studio Critiques |
1
|
20
|
20
|
Portfolio |
0
|
||
Homework / Assignments |
0
|
||
Presentation / Jury |
0
|
||
Project |
0
|
||
Seminar / Workshop |
0
|
||
Oral Exam |
0
|
||
Midterms |
1
|
20
|
20
|
Final Exam |
1
|
20
|
20
|
Total |
150
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
1
|
2
|
3
|
4
|
5
|
||
1 | To have adequate knowledge in Mathematics, Science and Computer Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems. |
|||||
2 | To be able to identify, define, formulate, and solve complex Computer Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose. |
|||||
3 | To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose. |
|||||
4 | To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Computer Engineering applications; to be able to use information technologies effectively. |
|||||
5 | To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Computer Engineering research topics. |
|||||
6 | To be able to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; to be able to work individually. |
|||||
7 | To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions. |
|||||
8 | To have knowledge about global and social impact of Computer Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Computer Engineering solutions. |
|||||
9 | To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications. |
|||||
10 | To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development. |
|||||
11 | To be able to collect data in the area of Computer Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1) |
|||||
12 | To be able to speak a second foreign language at a medium level of fluency efficiently. |
|||||
13 | To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Computer Engineering. |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
NEWS |ALL NEWS
Home kitchens will be like ‘restaurant kitchens’
Esra-Melis Sarıhan sisters, graduates of Izmir University of Economics (IUE), developed an application called ‘Yedir’ that will bring home cooks and food
She became one of the 10 most successful women in the Middle East
Melda Akın, a graduate of Department of Computer Engineering, Izmir University of Economics (IUE), was named one of the 10 most successful
Watch out for pandemic scams
Fake job postings that promise people to work from home have been the latest tactic of scammers, who are looking for ways