COURSE UNIT TITLE

: ECONOMIC OPTIMIZATION TECHNIQUES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IKT 6623 ECONOMIC OPTIMIZATION TECHNIQUES ELECTIVE 3 0 0 6

Offered By

Economics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSOCIATE PROFESSOR KERIM ESER AFŞAR

Offered to

Economics

Course Objective

The aim of this course is to teach microeconomic and macroeconomic issues and variables, the maximum, minimumand optimumcalculation.

Learning Outcomes of the Course Unit

1   To be abletolearnmaximum, minimum and optimumconcepts in economics
2   To be abletolearnlinearfunctionsused in linearprogramming
3   To be abletolearnnon- linearfunctions with maximum, minimum and optimum concepts
4   To be abletolearnoptimizationsubjectwithlinearprıgramming
5   To be abletolearnto calculatethe optimalPrimaland DualProblemssize ofthe country as a macroeconomic solution

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Maximum, Minimumand OptimumConcepts in Economics
2 LinearFunctions and TheirDerivatives
3 Non-linearfunctions:Maximum,minimum (optimum) and its derivatives
4 Non-linearfunctions,derivatives andillustrations
5 DrawingFunctions, Asymptotes, convexity, concavity
6 Functions of Several Variables localmaximum andlocalminimum
7 Functions of twovariable sconditional maximum and minimum
8 Functions of two variables conditional maximum and minimum(Lagrangefunction)
9 Functions oft wovariables conditional maximum and minimum(Lagrangefunction)
10 The useof linear programming optimization (Midterm exam will be done outside of course hours).
11 The useof linear programming optimization
12 Implementation of Linear Programming to macroeconomicProduction Problems
13 PrimalProblem solving(Quantitysolution)
14 Dual Problem solving (Pricesolution)

Recomended or Required Reading

Main References
Ahmet Kılıçbay, Kantitatif Iktisat Teorisi ve Politikası, Istanbul, 1970
Mustafa Özateşler-Ibrahim Hasgür, Matematik I, Izmir, 1986
Mustafa Özateşler-Ibrahim Hasgür, Matematik II, Izmir, 1987
OtherReferences
Mustafa Özateşler, Ekonomi Bilimi I, Izmir, 2000
Mustafa Özateşler, Ekonomi Bilimi II Makroekonomi, Izmir, 2009
Osman Halaç, Kantitatif Karar Verme Teknikleri, (Yöneylem Araştırması), Istanbul, 1978.
Aydın Aydıncıoğlu, Yönetim Ekonomisi,Kantitatif-Ekonomik Karar Modelleri, Istanbul,1976
Yılmaz Tulunay, Matematik Programlama ve Işletme uygulamaları, Istanbul, 1980
Yüksel Ülken Fiyat Teorisi, Istanbul, 1984
Ve konuyla ilgili diğer makale, yazı ve kitaplar

Planned Learning Activities and Teaching Methods

Classroomlessonsandsample problemssolvedby explainingthe economicoptimization ofa mathematicaltopics.to provide education forstudents, homeworkis givento solvethe problemsin different ways.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.20 + FIN* 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.20 + RST* 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

Midterm and final exams can examine the theoretic knowledges of students. Midterm assigment is a research paper that students can use their theoretic knowledges in this

Assessment Criteria

Final %50 Midterm assigment % 20 Midterm %30

Language of Instruction

Turkish

Course Policies and Rules

Attendance is mandatory to learn the course. During the course term students will be based on class participation.

Contact Details for the Lecturer(s)

mert.ural@deu.edu.tr

Office Hours

Tuesday 16.00-17.00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparation for final exam 1 20 20
Preparing assignments 1 15 15
Preparations before/after weekly lectures 14 4 56
Preparation for midterm exam 1 15 15
Final exam 1 1 1
Mid-termexam 1 1 1
TOTAL WORKLOAD (hours) 150

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9
LO.155
LO.255555555
LO.3555
LO.455
LO.5