Course Details

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Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
6IE395DECISION & RISK ANALYSIS3+0+03515.08.2025

 
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program INDUSTRIAL ENGINEERING
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course • Explain how people make decisions and decision-making traps
• Apply multi-criteria decision analysis tools such as multi-attribute utility theory and analytic hierarchy process
• Use multi-objective optimization and goal programming as a decision and risk analysis tool
Course Content Introduction to decision analysis, multi-criteria decision analysis, and multi-objective optimization.
Multi-attribute utility theory, analytic hierarchy process, and decision tree.
Multi-objective optimization and goal programming.
Course Methods and Techniques The course will be held in class face-to-face. CANVAS will be used for all announcements, course materials, links to additional lecture videos and other materials. You are responsible to follow the CANVAS regularly and study the lecture notes and watch the shared video links before the class.
We will be using various tools for active learning to take place. This is also a student-driven course. It is your responsibility to participate actively in class discussions. You are not graded on whether you agree or disagree with the instructor or with each other. Evaluation of class participation will be based on your ability to raise and answer important issues, contribute ideas or insights, build upon the ideas of others, ask questions to presenters, etc.
By actively participating in the class discussions, you can sharpen your insights and those of your classmates.
Both the quality and frequency of your participation will count towards your active participation grade. Please note that high-quality or relevant contributions will earn you a higher participation grade than frequent but insignificant contributions. Also, you will not get any class participation points for just being present in class. Class attendance is a necessary but not sufficient condition for scoring highly on class participation.
Prerequisites and co-requisities ( IE212 ) and ( IE221 )
Course Coordinator Asist Prof.Dr. Rukiye Kaya https://avesis.agu.edu.tr/rukiye.kaya rukiye.kaya@agu.edu.tr
Name of Lecturers Asist Prof.Dr. RUKİYE KAYA
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Chelst K, Canbolat YB. Value-Added Decision Making for Managers, CRC Press Taylor and Francis Group, 2012.
? Kirkwood CW. Strategic Decision Making: Multiobjective Decision Analysis with Spreadsheets, Duxbury Press, Belmont, CA, 1997.
Cohon JL. Multiobjective Programming and Planning, Academic Press, 1978.
Course Notes CANVAS

Course Category
Engineering %100

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı 1 % 25
Quiz/Küçük Sınav 2 % 10
Ödev 1 % 5
Proje/Çizim 1 % 20
Sunum/Seminer 1 % 10
Final examination 1 % 30
Total
7
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Araştırma Ödevi 1 5 5
Yazılı Sınav 1 10 10
Grup Sunumu 1 5 5
Grup Projesi 1 20 20
Ev Ödevi 1 3 3
Sınıf İçi Aktivitesi 3 1 3
Proje 1 20 20
Ders dışı çalışma 14 2 28
Yüz Yüze Ders 14 3 42
Final Sınavı 1 20 20
Total Work Load   Number of ECTS Credits 5 156

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Discuss the decision-making traps
2 Apply multi-attribute utility theory and analytic hierarchy process for decision analysis and risk analysis and management
3 Performs and implements risk analyzes using single- and multi-objective decision trees.
4 Make multi-objective optimization and goal programming for decision-making problems in continuous/discrete space
5 Apply risk analysis and management tools for decision making processes

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to Decision Making and Risk Analysis Review the lecture notes Canvas
2 Decision Traps Ders notlarını gözden geçir Canvas
3 Structure Decisions with Multiple Objectives Influence Diagrams Review the lecture notes Canvas
4 Multi Attribute Utility Theory Review the lecture notes Canvas
5 Multi Attribute Utility Theory 2 Review the lecture notes CANVAS
6 Multi Attribute Utility Theory-Sensitivity Analysis Review the lecture notes CANVAS
7 AHP Review the lecture notes canvas
8 Active learning week Review the lecture notes CANVAS
9 Value-Added Risk Management Framework and Strategies Review the lecture notes Canvas
10 Decisions with Uncertainty: Decision Trees Review the lecture notes Canvas
11 Decisions with Uncertainty: Decision Trees 2 Review the lecture notes canvas
12 Structured Risk Management and Value of Information; Risk Attitude Review the lecture notes Canvas
13 Structured Risk Management and Value of Information; Risk Attitude 2 Review the lecture notes CANVAS
14 Multi-Objective Optimization and Goal Programming Review the lecture notes CANVAS

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
C1 2 4 3 2 1 3 1
C2 4 4 5 5 5 3 3 1 3 2
C3 4 4 4 4 5 3 3 1 3 2
C4 4 4 4 4 4 3 3 1 3 2
C5 4 4 5 5 4 3 3 1 3 2

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
  https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=78818&lang=en
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