Ders Planı

CLASS 1

Lesson plan /

Lesson Information

Course Credit
Course ECTS Credit
Teaching Language of Instruction	İngilizce
Level of Course	Bachelor's Degree, TYYÇ: Level 6, EQF-LLL: Level 6, QF-EHEA: First Cycle
Type of Course
Mode of Delivery	Face-to-face
Does the course require compulsory or optional work experience?
Course Coordinator	Prof. Dr. RAFET AKDENİZ
Instructor (s)
Course Assistant

Purpose and Content

The aim of the course	The aim of the course, to enable students to use the multicriteria decision making methods (MCDM) by employing quantitative methods. Accordingly, in order to make business decisions using ranking irregularities, ELECTRE methods, the Analytic Hierarchy Process (AHP), decision-making applications are used to identify the variables and their suitability ratings for decisions. Students will be able to use Multi-criteria decision making techniques, partially or completely be able to rank the alternatives, and make decisions under conditions of uncertainty and high risk.
Course Content	Multi-Criteria Decision Making (MCDM) course is organised in five modules. It then explains the classification methods viz. ELECTRE-TRI, Kohonen Neural Networks. It then focuses on Distance, Outranking, Utility and Fuzzy system based MCDM methods. It then focuses on the Group Decision Making. This course uses case studies related to application of multi criteria decision making for effective learning to manage modern business firms and face challenges in competitive markets.

The aim of the course

The aim of the course, to enable students to use the multicriteria decision making methods (MCDM) by employing quantitative methods. Accordingly, in order to make business decisions using ranking irregularities, ELECTRE methods, the Analytic Hierarchy Process (AHP), decision-making applications are used to identify the variables and their suitability ratings for decisions. Students will be able to use Multi-criteria decision making techniques, partially or completely be able to rank the alternatives, and make decisions under conditions of uncertainty and high risk.

Course Content

Multi-Criteria Decision Making (MCDM) course is organised in five modules. It then explains the classification methods viz. ELECTRE-TRI, Kohonen Neural Networks. It then focuses on Distance, Outranking, Utility and Fuzzy system based MCDM methods. It then focuses on the Group Decision Making. This course uses case studies related to application of multi criteria decision making for effective learning to manage modern business firms and face challenges in competitive markets.

Learning Outcomes

Adequate knowledge in mathematics, physical sciences and the computer engineering subjects of individual branches; the ability to implement theoretical and practical knowledge in the respective areas to modeling and solving computer engineering problems.
Ability to reflect the developments in Information and Communication Technologies to the applications of Information Technology.
Ability to identify, define, formulate and solve complex computer engineering problems; ability to select and implement the appropriate analysis and modeling methods in this respect.
Ability to design experiments for analysing computer engineering problems, to conduct experiments, to collect data, to analyse and interpret the results.
Ability to design a complex informtacis system, process, device or product to meet specific requirements under realistic restrictions and conditions; ability to implement the modern design methods for this purpose.
Ability to use, choose and develop modern techniques and means required for computer engineering applications; ability to use information technologies effectively.
Ability to work effectively in interdisciplinary and multi-disciplinary teams; ability to work individually..
Knowledge of applications in business life like project management, risk management and change management; awareness about entrepreneurship, innovativeness and sustainable development.
Awareness of the necessity of lifelong learning; ability to reach information, follow the latest developments in science and technology; ability to ensure self-renewal perpetually.
Ability to communicate efficiently both in oral and written ways in Turkish; knowledge of at least one foreign language; ability to effectively prepare reports and understand written reports, prepare design and production reports, effective presentation, giving and receiving clear and understandable instructions.
Knowledge on the effects of informatics applications on health, environment and safety in terms of universal and social aspects and information about the problems of the era; awareness on the legal results of informatics solutions.
Acting in line with ethical principles, sense of professional and ethical responsibility; knowledge on the standards of engineering applications.

Weekly Course Subjects

1	Introduction to MCDM, The need for decision making, Key figures in decision making, Manegerial decision modeling.
2	Decision Making Under Uncertainty, Maximax Criterion, MaximinCriterion, Criterion of Realism, Minimax regret.
3	Introduction to MCDM, MCDM applications, Normalization methods, Simple Additive Weighting Method.
4	Weighted Sum Method (WSM), Weighted Product Method (WPM), WASPAS method
5	Analytic Hierarchy Method (AHP) and Case study
6	Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method and Case study
7	ELECTRE (Elemination and Choice Translating Reality English) method
8	Midterm Exam
9	MCDM method and application
10	MCDM method and application
11	Presentations(Assignment)
12	Presentations(Assignment)
13	Presentations(Assignment)
14	Presentations(Assignment)

Resources

Text book
(1).Raju K.S ., Nagesh Kumar D.,(2014). Multicriterion Analysis in Engineering and
Management, Prentice Hall of India (PHI) Learning Pvt. Ltd, New Delhi.
Supplementary Materials
(1). Dursun, M, Karsak, E. E.,Karadayi, M.A., (2011). A fuzzy multi-criteria group decision
making framework for evaluating health-care waste disposal alternatives, Expert Systems
with Applications,38,11453–11462.
(2).Gajpal.P.P., Ganesh, L.S.,Rajendran, C., (1994). Criticality analysis of spare parts using
the analytic hierarchy process, International Journal of Production Economics, 35, 293-297.
(3).Jong Chuu, S, (2009). Selecting the advanced manufacturing technology using fuzzy
multipleattributes group decision making with multiple fuzzy information, Computers &
Industrial Engineering, 57, 1033–1042.
(4).Kannan,G., Pokharel, S., Sasi Kumar, P., (2009). A hybrid approach using ISM and
fuzzy TOPSIS for the selection of reverse logistics provider, Resources, Conservation and
Recycling, 54, 28–36.

CLASS 1

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Lesson Information

Purpose and Content

Learning Outcomes

Weekly Course Subjects

Resources

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