GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
MULTI-CRITERIA DECISION MAKING/5571307
Course Title: MULTI-CRITERIA DECISION MAKING
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
This course provide students to improve the quality of the decisions they make in organizational and personal decisions.
It is planned to improve students' decision making skills, their ability to analyze problems systematically, and their confidence in their decisions.
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Decision Making, Decision Making Process, Decision Support Approaches, Multi Criteria Decision Making, History, Types of Problems
2. Week  Multi Objective Decision Making and Multi-Attribute Decision Making Criteria Normalization, Measurement and Measurement Techniques of Preferences
3. Week  Multi-Criteria Ranking and Rating: cardinal and non-cardinal models, Dominance - Pareto, Lexical Sort, Minimax, Maximin, SAW and SWP
4. Week  Compromise model:TOPSIS method: computer applications
5. Week  Hierarchical structures: Analytic Hierarchy Process (AHP), consistency analysis, computer applications.
6. Week  Decision Making under Dependence and Feedback: Analytic Network Process, Impact matrix, Sensitivity analysis, DEMATEL
7. Week  Midterm Exam
8. Week  Top Rating (Compliance-Divergence) Methods: ELECTRE methods, Electre I, Iv, Is, II, III, IV, ELECTRE-Tri, Computer Applications (Excel, ELECTRE Is)
9. Week  Top Rating (Compliance-Divergence) methods: PROMETHEE, PROMETHEE I and PROMETHEE II, GAIA plane, Sensitivity Analysis, PROMETHEE GDSS, FlowSort
10. Week  SMAA (JSMAA), Multi-Criteria Performance Measurement, Data envelopment analysis (DEA), Dynamic DEA Window Analysis, win4deap Frontier Analyst
11. Week  Multi Criteria Classification Problem: UT, UTADIS, Application, MACBETH, LP-MACBETH, Value tree, sensitivity analysis, Software: M-MACBETH
12. Week  Multi-attribute Utility Theory (MAUT), Simple Multi Attribute Rating Technique (SMART), The UTA method, UTAGMS, GRIP, VİKOR, TODIM
13. Week  Other ranking methods: QUALIFLEX, régime, ORESTE ARGUS, EVANİX, TACTIC, MELCHIOR
14. Week  Other ranking methods: MAP PAC & PRAGMA, IDRA & PACMAN
15. Week  Fuzzy Multiple Criteria Decision Making, Multi Purpose Optimization: Goal Programming, Extensions of the GP: Weighted GP, lexicographic GP, GP Chebysh
16. Week  Final Exam
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
40
 Assignment
1
20
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
60
 Percentage of Final Exam to Total Score  
40
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
0
 Searching in Internet and Library
4
5
20
 Material Design and Implementation
0
 Report Preparing
5
10
50
 Preparing a Presentation
2
5
10
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
2
10
20
 Final Exam and Preperation for Final Exam
3
11
33
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
175
 TOTAL WORKLOAD / 25: 
7
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1X
2
3
4
5X
6
7
8
9X
10X
11
12X
 -- NAME OF LECTURER(S)
   (Prof. Metin DAĞDEVİREN , Prof. Mehmet KABAK and other relevant faculty members)
 -- WEB SITE(S) OF LECTURER(S)
   (websitem.gazi.edu.tr/metindag , websitem.gazi.edu.tr/mkabak)
 -- EMAIL(S) OF LECTURER(S)
   (metindag@gazi.edu.tr , mkabak@gazi.edu.tr)