Knows the utility axioms, represents a decision problem as a lottery and calculates the expected utility of this lottery. Evaluates a decision maker's utility function and uses it to solve a given decision tree.
Prerequisite(s)
IE3101 Introduction to Probability
Corequisite(s)
-
Special Requisite(s)
-
Instructor(s)
Professor Murat Ermiş
Course Assistant(s)
Schedule
The course is not offered this semester.
Office Hour(s)
The course is not offered this semester.
Teaching Methods and Techniques
-Lecture, question-answer, discussion, problem solving
Principle Sources
- Clemen, R.T., and Reilly, T., 2013. Making Hard Decisions with Decision Tools, 3rd Edition, Cengage Learning.
Other Sources
- Taylor B.W., 2019. Introduction to Management Science, 13th Edition, Pearson Education Inc., New Jersey.
- Balakrishnan N., Render B., Stair R.M. Jr., 2017. Managerial Decision Modeling with Spreadsheets, 4th Edition, Prentice-Hall, New Jersey.
- Goodwin P. and Wright G., 2014. Decision Analysis for Management Judgment, 5th Edition, John Wiley & Sons, New York.
- Saaty T.L. and Vargas L.G., 2013. Decision Making with the Analytic Network Process, 2nd Edition, Springer, New York.
- Saaty T.L., 2005. Theory and Applications of the Analytic Network Process, RWS Pub.,Pittsburgh.
- Saaty T.L., 2012. Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World, 3rd Edition, RWS Pub., Pittsburgh.
- Keeney R.L., 2009. Value Focused Thinking: A Path to Creative Decision Making, Harvard University Press, London.
- Koksalan M., Wallenius J., and Zionts, S., 2011. Multiple Criteria Decision Making: From Early History to the 21st Century, World Scientific Publishing Company, New Jersey.
- Parnell, G.S., Bresnick, T.A., Tani, S.N., and Johnson E.R., 2013. Handbook of Decision Analysis, Wiley, New Jersey.
- Ishizaka, A. and Nemery, P., 2013. Multi-criteria Decision Analysis: Methods and Software,Wiley, West Sussex.
Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction to Decision Theory
Lecture, question-answer, discussion, problem solving
2. Week
Elements of Decision Problems
Lecture, question-answer, discussion, problem solving
3. Week
Structuring of decisions, decision making under uncertainty and risk
Lecture, question-answer, discussion, problem solving
4. Week
Decision Trees, Making Choices
Lecture, question-answer, discussion, problem solving
5. Week
Value of Additional Information and Perfect Information
Case Study
6. Week
Utility Theory
Lecture, question-answer, discussion, problem solving
7. Week
Multicriteria Decision Making
Lecture, question-answer, discussion, problem solving
8. Week
Modelling
Lecture, question-answer, discussion, problem solving
9. Week
Solving the problem (SAW, WP, TOPSIS)
Lecture, question-answer, discussion, problem solving
10. Week
Analytical Hierarchy Process (AHP)
Lecture, question-answer, discussion, problem solving
11. Week
Analytical Network Process (ANP), Super Decisions
Lecture, question-answer, discussion, problem solving
12. Week
Outranking Methods (PROMETHEE, ELECTRE)
Lecture, question-answer, discussion, problem solving
13. Week
Group Decision Making
Lecture, question-answer, discussion, problem solving
14. Week
Term Project Presentations
Presentationr, discussion
15. Week
Final
16. Week
Final
17. Week
Final
Assessments
Evaluation tools
Quantity
Weight(%)
Homework / Term Projects / Presentations
3
30
Project(s)
1
30
Final Exam
1
40
Program Outcomes
PO-1
Knowledge about management processes and management skills
PO-2
Knowledge and application skills related to the methods and competencies required for solving engineering problems
PO-3
Knowledge about developing areas of manufacturing and service sectors
PO-4
Ability to work in multi-disciplinary engineering teams
PO-5
Experience and knowledge of scientific research and publishing within the frame of academic ethics
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, calculate posterior probabilities in decisions where sample information exists and decide whether sample information is required.
LO-3
Knows the utility axioms, represents a decision problem as a lottery and calculates the expected utility of this lottery. Evaluates a decision maker's utility function and uses it to solve a given decision tree.
LO-4
Understands the Analytic Hierarchy Process (AHP) as a tool to solve multi-criteria decision-making problems and applies it to problems.
LO-5
For the competing decision makers, applies game theory and chooses optimal strategies for each player.
