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GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of STATISTICS and COMPUTER SCIENCES
Statistics-Joint Doctorate
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FBE
GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of STATISTICS and COMPUTER SCIENCES / Statistics-Joint Doctorate
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IST7023Multi Criteria Decision Making3+0+0ECTS:7.5
Year / SemesterSpring Semester
Level of CourseThird Cycle
Status Elective
DepartmentDEPARTMENT of STATISTICS and COMPUTER SCIENCES
Prerequisites and co-requisitesNone
Mode of Delivery
Contact Hours14 weeks - 3 hours of lectures per week
LecturerDr. Öğr. Üyesi Serkan AKBAŞ
Co-LecturerProf. Dr. Türkan ERBAY DALKILIÇ
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
Explaining the methods for solving Multiple Criteria Decision Making Problems, applications in practice.
 
Programme OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
PO - 1 : form the mathematical model of an multi-criteria problem.1,2,4,51,3,5
PO - 2 : solve the multi-criteria problem by using the technics that given in course.1,2,4,51,3,5
PO - 3 : by modeling the multi-criteria and limited problems in other disciplines reach a solution.1,2,4,51,3,5
PO - 4 : solve the multi-criteria problems that they modelled mathematically using the package program.1,2,4,51,3,5
PO - 5 : bring economic comments to solving the multi-criteria problems 1,2,4,51,3,5
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome

 
Contents of the Course
Models and principles of modeling in operational research method, multi criteria simplex method, network analysis, queuing and inventory models, goal programing, dynamic and non-dynamic programming, decision analysis.
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Basic concepts of multi criteria decision making.
 Week 2Mathematical structure of multi criteria decision models.
 Week 3Multi-purpose simplex method (Zeleyn Algorithm).
 Week 4The basic concepts of game theory.
 Week 5Superior options principle.
 Week 6Absolute criteria method.
 Week 7Interactive methods: Stem methods
 Week 8Mid-term exam
 Week 9Interactive methods: Belenson-Kapor method.
 Week 10Interactive methods: Zionts-Wallerius method.
 Week 11Mediation programming.
 Week 12Goal programming.
 Week 13Queuing and inventory models.
 Week 14Dynamic programming.
 Week 15Non-dynamic programming
 Week 16End-of-term exam
 
Textbook / Material
1Hamdy A. TAHA, 2000; Yöneylem Araştırması, Literatür Yayınları, İstanbul.
 
Recommended Reading
1Charnes, A., 1991;Management Models and Industrial Applications of Linear Programming, John Wiley and Sons, London.
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 22/11/2013 2 50
End-of-term exam 16 10/01/2014 2 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Sınıf dışı çalışma 5 14 70
Ödev 4 14 56
Total work load126