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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS CSC 5010 FUZZY MULTICRITERIA DECISION TECHNIQUES ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR AYŞE ÖVGÜ KINAY

Offered to

Ph.D. in Computer Science (English) Computer Science Artificial Intelligence and Intelligent Systems

Course Objective

In this course, it is aimed to give students knowledge of fuzzy multi-attribute and multi-objective decision making methodologies.

Learning Outcomes of the Course Unit

1   Have a good understanding of the fuzzy logic. 2   Have a good understanding of the construction, and analysis of discrete multicriteria decision-making models. 3   Have a good understanding of the construction, and analysis of continuous multicriteria decision-making models. 4   Have a good understanding of the construction of fuzzy preference relations. 5   Be able to decision making with fuzzy information.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 The definition of decision-making problems Concept of fuzzy sets 2 Concept of fuzzy sets (cont.) 3 Analytic Hierarchy Process (AHP) Fuzzy AHP 4 Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Fuzzy TOPSIS 5 VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) Fuzzy VIKOR 6 Elimination and Choice Translating Reality (ELECTRE) Fuzzy ELECTRE 7 Analytic Network Process (ANP) Fuzzy ANP 8 Midterm exam 9 Multi-attribute utility theory (MAUT) Fuzzy MAUT 10 Simple Additive Weighting (SAW) Fuzzy SAW 11 Comparison of Multi-Criteria Decision Methods (MCDM) and examination of co-use of methods 12 Comparison of Multi-Criteria Decision Methods (MCDM) and examination of co-use of methods (cont.) 13 Other MCDM presentations 14 Other MCDM presentations (cont.)

Recomended or Required Reading

Textbook(s): Witold Pedrycz, Petr Ekel, Roberta Parreiras, Fuzzy Multicriteria Decision-Making: Models, Methods and Applications, Wiley, 2010. Supplementary Book(s): Kahraman, C.(Editor). Fuzzy Multi-Criteria Decision Making: Theory and Applications with Recent Developments, Springer, 2008.

Planned Learning Activities and Teaching Methods

Lecture format, built around the textbook readings with numerous examples chosen to illustrate theoretical concepts.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 PRS PRESENTATION 2 FIN FINAL EXAM 3 FCG FINAL COURSE GRADE PRS * 0.40 + FIN * 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) PRS * 0.40 + RST * 0.60 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

ovgu.tekin@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 6 78 Preparing presentations 13 3 39 Preparation for final exam 13 3 39 Project Final Presentation 1 1 1 Final 1 1,5 2 TOTAL WORKLOAD (hours) 198

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 5 5 5 5 5 LO.2 5 5 5 5 5 LO.3 5 5 5 5 5 LO.4 5 5 5 5 5 LO.5 5 5 5 5 5