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FACULTY of ARCHITECTURE / DEPARTMENT of ARCHITECTURE /
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EKO 324Decision Making and Game Theory3+0+0ECTS:5
Year / SemesterSpring Semester
Level of CourseFirst Cycle
Status Compulsory
DepartmentDEPARTMENT of ECONOMETRICS
Prerequisites and co-requisitesNone
Mode of DeliveryFace to face
Contact Hours14 weeks - 3 hours of lectures per week
LecturerProf. Dr. Tuba YAKICI AYAN
Co-LecturerNone
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
This course aims to enhance the students' ability to think strategically in complex interactive environments and to provide them with an understanding of the use decision and risk analysis for evaluation of real world projects and opportunities
 
Learning OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
LO - 1 : determine numerical methods which can be used to make choice among multiple alternatives.1,2,3,4,5,6,71
LO - 2 : define similar and different features of decision making methods1,2,3,4,5,6,71
LO - 3 : solve decision making problems by means of learned methods.1,2,3,4,5,6,71
LO - 4 : select best fit method for decision environment1,2,3,4,5,6,71
LO - 5 : make the right decision by means of learned methods1,2,3,4,5,6,71
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), LO : Learning Outcome

 
Contents of the Course
Decision making under uncertainty : The maximin criterion, the maximax criterion, the Laplace criterion, the Hurwitz criterion, the savage criterionDecision rules in risk environment: The maximum possibility criterion, the expected minimum opportunity cost, value of experimentationDecision trees : Drawing a decision tree, evaluating the decision tree, calculating the tree values, calculating the value of uncertain outcome nodes, calculating the value of decision nodes, making decisionGame theory: The formulation of two-person, zero-sum games, solving simple games, games with mixed strategies, graphical solution procedure, solving by linear programming. Queuing theory: Basic structure of queuing models, queuing models involving exponential distribution, queuing models based on the birth-death process, queuing models involving nonexponential distributions, queuing networks.
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Course objectives and outlines
 Week 2Decision making under uncertainty : The maximin criterion, the maximax criterion, the Laplace criterion, the Hurwitz criterion, the savage criterion
 Week 3Decision rules in risk environment: The maximum possibility criterion, the expected minimum opportunity cost, value of experimentation
 Week 4Decision trees : Drawing a decision tree, evaluating the decision tree, calculating the tree values, calculating the value of uncertain outcome nodes, calculating the value of decision nodes, making decision
 Week 5Game theory: The formulation of two-person, zero-sum games, solving simple games, games with mixed strategies
 Week 6Graphical solution procedure
 Week 7Solving by linear programming
 Week 8Queuing theory: Basic structure of queuing models
 Week 9Mid-term exam
 Week 10Queuing models involving exponential distribution, queuing models based on the birth-death process
 Week 11Queuing models involving nonexponential distributions
 Week 12Queuing networks, single server queuing models
 Week 13Multiple server queuing models
 Week 14Exercises about waiting lines
 Week 15Review
 Week 16End-of-term exam
 
Textbook / Material
1Clemen, R. , Reilly, T. , 2004, Making Hard Decisions with Decision Tools Suite, 1st ed, Duxbury Pres.
 
Recommended Reading
1Hillier, F. , Liberman, G. , 2005, Introduction to Operations Research, 8 st ed. , Mc Graw-Hill Science.
2Neumann, J. , Morgenstern, O. , 2004, Theory of Games and Economics Behavior, 16th ed. , Princeton University Press.
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 04/2016 1 50
End-of-term exam 16 05/2016 1 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 3 14 42
Sınıf dışı çalışma 4 14 56
Arasınav için hazırlık 8 2 16
Arasınav 1 1 1
Ödev 1 1 1
Dönem sonu sınavı için hazırlık 11 3 33
Dönem sonu sınavı 1 1 1
Total work load150