Course Details

DECISION ANALYSIS

IE542

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Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
3IE542DECISION ANALYSIS3+0+037,5

Course Details
Language of Instruction English
Level of Course Unit Master's Degree
Department / Program INDUSTRIAL ENGINEERING
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course • To understand the fundamentals of decision-making under uncertainty and risk.
• To apply decision analysis techniques to real-world problems.
• To evaluate different decision-making strategies and their implications.
• To utilize multi-criteria decision-making tools and decision support systems.
Course Content This course provides an in-depth exploration of decision analysis concepts, focusing on tools and methodologies for making informed decisions in uncertain and complex environments. Topics include decision theory, utility theory, multi-criteria decision-making, Bayesian analysis, and risk analysis. The course emphasizes practical applications through case studies and real-world examples, incorporating the use of decision support systems and software tools
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 None
Course Coordinator Asist Prof.Dr. Rukiye Kaya https://avesis.agu.edu.tr/rukiye.kaya rukiye.kaya@agu.edu.tr
Name of Lecturers None
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.
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 3 % 5
Proje/Çizim 1 % 20
Sunum/Seminer 1 % 10
Final examination 1 % 30
Total
9
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Araştırma Ödevi 3 10 30
Tartışma 5 1 5
Yazılı Sınav 1 20 20
Grup Sunumu 1 5 5
Ev Ödevi 1 3 3
Sınıf İçi Aktivitesi 5 2 10
Sunum için Hazırlık 1 3 3
Sunum 1 1 1
Proje 1 20 20
Kısa Sınav 2 3 6
Okuma 3 5 15
Ders dışı çalışma 14 2 28
Takım/Grup Çalışması 3 2 6
Öğretici Sunum/Açıklama 5 1 5
Yüz Yüze Ders 14 3 42
Final Sınavı 1 25 25
Total Work Load   Number of ECTS Credits 7,5 224

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Understand the importance of modeling in risk analysis and system engineering.
2 Implements appropriate risk analysis and management process to problems.
3 Performs and implements risk analyzes using single- and multi-objective decision trees.
4 Implements appropriate multi-objective decision making techniques to problems.
5 Implements risk modeling and assesment to extreme events.
6 Applies fault tree, event tree, failure mode effect and analysis techniques.
7 Makes risk modeling and analysis of systems of dynamic systems and complex systems.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 The Role of Modeling in Systems Engineering and Risk Analysis Review the lecture notes Canvas
2 Basic Components of Mathematical Models Canvas
3 Basic Decision Analysis, Decision Trees and Probability Distribution Functions Canvas
4 Multi-Objective Decision Making Canvas
5 Multi-Objective Decision Making CANVAS
6 Risk Assessment of Extreme Events: Divided Multi-Objective Risk Method CANVAS
7 Midterm canvas
8 Multiobjective Statistical Method CANVAS
9 Risk, Uncertainty and Uncertainty Taxonomy Canvas
10 Active learning week Canvas
11 Multi-Objective Decision Tree Analysis canvas
12 Extreme Events Statistic Canvas
13 Multi-Stage, Multi-Objective Impact Analysis Method: Modeling of Dynamic Systems CANVAS
14 Combination of Multi-Objective Risk Method and Multi-Stage multiobjective Impact Analysis Method CANVAS
15 Fault Tree Analysis, Event Tree Analysis, System Reliability, Modeling Complex Systems of Systems


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
C1 1 2 1 5 5
C2 5 3 3 3 3
C3 5 4 2 3 3
C4 5 4 2 3 3
C5 5 4 2
C6 5 4 2 3 5 3 3 5
C7 5 4 2 5 5 3 5 5 3 5

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


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=77288&lang=en
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