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Information
| Code | EM0029 |
| Name | Multi-Criteria Decision Making Methods |
| Term | 2023-2024 Academic Year |
| Semester | . Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator |
Course Goal / Objective
The aim of this course is to deal with decision making and decision making under multi-criteria conditions, which are one of the most fundamental subjects of Industrial Engineering, to review the solution methods of multi-criteria decision-making problems, to examine the solutions for continuous and discrete multi-criteria decision-making problems.
Course Content
Brief overview to multiple criteria decision making problems. Multiple criteria decision making problems and solution methods. Multi-objective optimization models. Goal programming. Interactive approaches. Multiple criteria ranking and sorting techniques. Fuzzy logic applications. Multiple criteria decision making applications.
Course Precondition
None
Resources
Tzeng, Gwo-Hshiung, and Jih-Jeng Huang. Multiple attribute decision making: methods and applications. Chapman and Hall/CRC, 2011. Evans, Gerald William. Multiple criteria decision analysis for industrial engineering: methodology and applications. CRC Press, 2016. Zopounidis, C., & Doumpos, M. (Eds.). (2016). Multiple criteria decision making: Applications in management and engineering. Springer. Ravindran, A. R. (Ed.). (2016). Multiple criteria decision making in supply chain management. CRC Press.
Notes
Articles on the topics
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | To learn multi-criteria decision making methods |
| LO02 | Making multi-criteria decision making applications |
| LO03 | Learning and researching innovative decision making methods |
| LO04 | Having knowledge and skills in making decisions under fuzzy logic and uncertainty |
| LO05 | To learn multi-objective decision making methods |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Conducts scientific research in industrial engineering, understands, interprets and applies knowledge in his/her field domain both in-depth and in-breadth. | 3 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Keeps up with the recent changes and applications in the field of Industrial Engineering and examines and learns these innovations when necessary. | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Acquires detailed knowledge for methods and tools of industrial engineering and their limitations. | 4 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Identifies, gathers and uses necessary information and data. | |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Develops original definitions that will provide innovation to the field at the level of expertise for current and advanced information in the field based on graduate qualifications. | |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Designs and performs analytical modeling and experimental research and analyze/solves complex matters emerged in this process. | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Has the ability to develop/propose new and/or original ideas and methods, propose new solutions for designing systems, components or processes. | 5 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Designs Industrial Engineering problems, develops new methods to solve the problems and applies them. | |
| PLO09 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Works in multi-disciplinary teams, take a leading role and responsibility and develop solutions for complex problems. | |
| PLO10 | Yetkinlikler - Öğrenme Yetkinliği | Completes and applies the knowledge by using limited resources in scientific methods and integrates the knowledge in the field with the knowledge form various disciplines. | 5 |
| PLO11 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a foreign language in verbal and written communication at least B2 level of European Language Portfolio. | 3 |
| PLO12 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Presents his/her research findings systematically and clearly in oral or written forms in national and international platforms. | 4 |
| PLO13 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Understands social and environmental implications of engineering practice. | |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | Considers social, scientific and ethical values in data collection, interpretation and announcement processes and professional activities. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to multi-criteria decision making | General information on the subject | Öğretim Yöntemleri: Anlatım |
| 2 | Understanding the logic of multi-criteria decision making | General information on the subject | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 3 | Analytical hierarchy process method | Reading on the method | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 4 | Analytical network process method | Reading on the method | Öğretim Yöntemleri: Anlatım, Beyin Fırtınası, Örnek Olay |
| 5 | Entropy method | Reading on the method | Öğretim Yöntemleri: Anlatım, Beyin Fırtınası, Örnek Olay |
| 6 | TOPSIS method | Reading on the method | Öğretim Yöntemleri: Anlatım, Beyin Fırtınası, Örnek Olay |
| 7 | VIKOR method | Reading on the method | Öğretim Yöntemleri: Anlatım, Beyin Fırtınası, Örnek Olay |
| 8 | Project Homework | Homework report | Ölçme Yöntemleri: Proje / Tasarım |
| 9 | ELECTRE method | Reading on the method | Öğretim Yöntemleri: Anlatım, Beyin Fırtınası, Örnek Olay |
| 10 | Fuzzy sets and numbers | Reading on the method | Öğretim Yöntemleri: Anlatım, Beyin Fırtınası, Örnek Olay |
| 11 | Rough sets | Reading on the method | Öğretim Yöntemleri: Anlatım, Tartışma |
| 12 | Gray relational analysis | Reading on the method | Öğretim Yöntemleri: Anlatım, Tartışma |
| 13 | Multi-objective optimization (introduction) | Reading on the mathematical modeling | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 14 | Multi-objective optimization (goal programming) | Reading on the mathematical modeling | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 15 | Multi-objective optimiziation (heuristic) | Reading on the heuristic methods | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 16 | Final Exam | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Final Exam | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||