Decision Making Analysis (MDES654) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Decision Making Analysis MDES654 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type N/A
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives This course aims to give the students the theory and practical tools of decision making with the purpose of aiding them during their graduate research.
Course Learning Outcomes The students who succeeded in this course;
  • 1. Students will have an overview of the literature and historical perspective of decision analysis. 2. Students will be able to resolve a decision making problem using the analytical tools of decision analysis. 3. Students will have an understanding of the utility theory. 4. Students will be able to formulate a real life situation with conflicting objectives as a decision making problem. 5. Students will acquire the ability to summarize a mathematical paper in front of an audience.
Course Content Conflicting objectives in decision making; decision problems under certainty; utility theory for single-attribute and multi-attribute problems in decision analysis; individual versus group decisions.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introductory and historical overview of decision making. Sample cases. Related pages of the textbook and other sources
2 Basic concepts. Decision trees... Related pages of the textbook and other sources
3 Multi-attribute problems under certainty. Domination, efficient frontier solutions, lexico-graphic ordering, indifference curves, value functions. Related pages of the textbook and other sources
4 Multi-attribute problems under certainty. Domination, efficient frontier solutions, lexico-graphic ordering, indifference curves, value functions. Related pages of the textbook and other sources
5 Problems under uncertainty. Utility Theory. Utility functions for single-attribute problems. Assessment of utility functions. Risk aversion. Related pages of the textbook and other sources
6 Problems under uncertainty. Utility Theory. Utility functions for single-attribute problems. Assessment of utility functions. Risk aversion. Related pages of the textbook and other sources
7 Problems under uncertainty. Utility Theory. Utility functions for single-attribute problems. Assessment of utility functions. Risk aversion. Related pages of the textbook and other sources
8 Problems under uncertainty. Utility Theory. Utility functions for single-attribute problems. Assessment of utility functions. Risk aversion. Related pages of the textbook and other sources
9 Midterm -
10 Multi-attribute problems under uncertainty. Utility independence. Assessment of multi-attribute utility functions. Additivity, multiplicativity and decomposition of utility functions. Hierarchical attributes for decision making. Related pages of the textbook and other sources
11 Multi-attribute problems under uncertainty. Utility independence. Assessment of multi-attribute utility functions. Additivity, multiplicativity and decomposition of utility functions. Hierarchical attributes for decision making. Related pages of the textbook and other sources
12 Multi-attribute problems under uncertainty. Utility independence. Assessment of multi-attribute utility functions. Additivity, multiplicativity and decomposition of utility functions. Hierarchical attributes for decision making. Related pages of the textbook and other sources
13 Overview of applications of decision making. Related pages of the textbook and other sources
14 Paper presentations -
15 Overall review -
16 Final exam -

Sources

Course Book 1. [1] R.L. Keeney and H. Raiffa, Decisions with Multiple Objectives: Preferences and Value Tradeoffs, Cambridge University Press, 1993.
Other Sources 2. [2] D.E. Bell, H. Raiffa, and A. Tversky, Decision Making: Descriptive, Normative, and Prescriptive Interactions, Cambridge University Press, 1988.
3. [3] R.L. Keeney, Value-Focused Thinking: A Path to Creative Decision Making, Harvard University Press, 1996.
4. [4] H. Raiffa, Decision Analysis: Introductory Lectures on Choices under Uncertainty, Addison-Wesley, 1968.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 3 25
Presentation 1 15
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 30
Toplam 6 100
Percentage of Semester Work 70
Percentage of Final Work 30
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Ability to expand and get in-depth information with scientific researches in the field of mechanical engineering, evaluate information, review and implement.
2 Have comprehensive knowledge about current techniques and methods and their limitations in Mechanical engineering.
3 To complete and apply knowledge by using scientific methods using uncertain, limited or incomplete data; use information from different disciplines.
4 Being aware of the new and developing practices of Mechanical Engineering and being able to examine and learn when needed.
5 Ability to define and formulate problems related to Mechanical Engineering and develop methods for solving and apply innovative methods in solutions.
6 Ability to develop new and/or original ideas and methods; design complex systems or processes and develop innovative/alternative solutions in the designs.
7 Ability to design and apply theoretical, experimental and modeling based researches; analyze and solve complex problems encountered in this process.
8 Work effectively in disciplinary and multi-disciplinary teams, lead leadership in such teams and develop solution approaches in complex situations; work independently and take responsibility.
9 To establish oral and written communication by using a foreign language at least at the level of European Language Portfolio B2 General Level.
10 Ability to convey the process and results of their studies systematically and clearly in written and oral form in national and international environments.
11 To know the social, environmental, health, security, law dimensions, project management and business life applications of engineering applications and to be aware of the constraints of their engineering applications.
12 Ability to observe social, scientific and ethical values in the stages of data collection, interpretation and announcement and in all professional activities.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration 1 24 24
Project
Report
Homework Assignments 3 4 12
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 8 8
Prepration of Final Exams/Final Jury 1 10 10
Total Workload 134