To learn the tools and techniques for analyzing complex business situations to make scientific decisions
Prerequisite(s)
IE3101 Introduction to Probability
Corequisite(s)
None
Special Requisite(s)
Attendance is mandatory; students who have attended less than 60% of classes will receive zero points from the term project regardless of their exam grades. Each student is expected to actively participate in classroom discussions and exercises.
Instructor(s)
Assist. Prof. Dr. Duygun Fatih Demirel
Course Assistant(s)
-
Schedule
Theory: Monday, 09:00-10:45, 2-B-11/13
Practice Session: Monday, 11:00-12:45, 2-B-11/13
Office Hour(s)
Wednesday, 11:00-11:45, Office 2-A-10
Teaching Methods and Techniques
-Lecture, question-answer, discussion, problem solving
Principle Sources
- R.T. Clemen and T. Reilly, Making Hard Decisions with DecisionTools, 2nd edition, Duxbury.
- H.A. Taha, Operations Research: An Introduction, 10th edition, Prentice Hall.
- W. L. Winston, (2004). Operations Research: Apllications and Algorithms. 4th Edition. Thomson Brooks/Cole, Belmont.
- M. Peterson, (2009). An Introduction to Decision Theory. Cambridge University Press.
Other Sources
-
Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction to Decision Theory, Decision Making under Certainty, Introduction to MCDM
Lecture, question-answer, discussion, problem solving
2. Week
AHP, TOPSIS
Lecture, question-answer, discussion, problem solving
3. Week
Goal Programming, Data Envelopment Analysis
Lecture, question-answer, discussion, problem solving
4. Week
Case Studies on AHP, TOPSIS, Goal Programming, and Data Envelopment Analysis, Decision Making under Uncertainty, Decision Making under Risk, Introduction to Decision Trees
Lecture, question-answer, discussion, problem solving
5. Week
Decision Trees: Cumulative Risk Profiles, Multiobjective Problems in Decision Trees
Lecture, question-answer, discussion, problem solving
Lecture, question-answer, discussion, problem solving
7. Week
Article Presentations
Lecture, question-answer, discussion
8. Week
Decision Trees: Value of Information, Case Studies on Decision Trees
Lecture, question-answer, discussion, problem solving
9. Week
Midterm Exam
10. Week
Utility Theory
Lecture, question-answer, discussion, problem solving
11. Week
Utility Theory
Lecture, question-answer, discussion, problem solving
12. Week
Project Presentations
Lecture, question-answer, discussion
13. Week
Game Theory
Lecture, question-answer, discussion, problem solving
14. Week
Game Theory
Lecture, question-answer, discussion, problem solving
15. Week
Final
-
16. Week
Final
-
17. Week
Final
-
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
35
Quizzes
2
5
Project(s)
1
15
Article Presentations
1
5
Final Exam
1
40
Program Outcomes
PO-1
Ability to apply theoretical and practical knowledge gained by Mathematics, Science and their engineering fields and ability to use their knowledge in solving complex engineering problems.
PO-2
Ability of determining, defining, formulating and solving complex engineering problems; for that purpose develop the ability of selecting and implementing suitable models and methods of analysis.
PO-3
Ability of designing a complex system, process, device or product under real world constraints and conditions serving certain needs; for this purpose ability of applying modern design techniques
PO-4
Ability of selecting and using the modern techniques and devices which are necessary for analyzing and solving complex problems in engineering implementations; ability of efficient usage of information technologies.
PO-5
Ability of designing experiments, conducting tests, collecting data and analyzing and interpreting the solutions to investigate of complex engineering problems or discipline-specific research topics.
PO-6
Ability of working efficiently in intra-disciplinary and multi-disciplinary teams; individual working ability and habits.
PO-7
Ability of verbal and written communication skills; and at least one foreign language skills, ability to write effective reports and understand written reports, ability to prepare design and production reports, ability to make impressive presentation, ability to give and receive clear and understandable instructions
PO-8
Awareness of importance of lifelong learning; ability to access data, to follow up the recent innovation in science and technology for continuous self-improvement.
PO-9
Conformity to ethical principles; knowledge about occupational and ethical responsibility, and standards used in engineering applications.
PO-10
Knowledge about work life implementations such as project management, risk management and change management; awareness about entrepreneurship and innovativeness; knowledge about sustainable development.
PO-11
Knowledge about effects of engineering applications on health, environment and security in global and social dimensions, and on the problems of the modern age in engineering; awareness about legal outcomes of engineering solutions.
Learning Outcomes
LO-1
Knows the elements of a decision problem, constructs the decision matrix or decision tree and decides based on different decision criteria.
LO-2
Distinguishes between prior and posterior probabilities; calculates posterior probabilities in a given decision-making problem and decides whether the experimental information is needed
LO-3
Knows the Utility axioms, represents a problem as a lottery and calculates expected utility (EU) of that lottery. Evaluates a decision maker's utility function and uses it to solve a given decision tree. Assesses the risk attitude of a decision maker by constructing its utility function.
LO-4
Evaluates a decision maker's attitudes based on game theory perspectives and uses game theory in decision making.
LO-5
Comprehends Analytical Hierarchy Process (AHP) and TOPSIS and similar techniques as tools to solve multicriteria decision problems and applies them to a given problem
