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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 6091 UNCONSTRAINED OPTIMIZATION TECHNIQUES ELECTIVE 3 0 0 6

Offered By

Econometrics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR IPEK DEVECI KOCAKOÇ

Offered to

Econometrics

Course Objective

Optimization is one of the major building blocks of decision-making. This course covers the mathematical modeling and solution of optimization problems by unconstrained optimization algorithms and with the help of computers.

Learning Outcomes of the Course Unit

1   To be able to form understand the basic principle of unconstrained optimization. 2   To be able to generate problem as a constrained optimization problem. 3   To be able to determine the objective function of the problem. 4   To be able to understand selection criterias of unconstrained optimization problem. 5   To be able to solve unconstrained optimization problem.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to Optimization 2 Introduction to mathematical modeling and Unconstrained Optimization 3 Introduction to Matlab Software package 4 Graphical Optimization-Matlab Application 5 Matlab Optimization Introduction to Toolbox 6 Newton Methods 7 Confidence Region Methods 8 Mid-term 9 Conjugate Gradient Methods 10 Quasi-Newton Methods 11 Optimization without deriatives 12 Least Squares Problems 13 Nonlinear Equations 14 Nonlinear Equations

Recomended or Required Reading

Jorge Nocedal Stephen J. Wright, Numerical Optimization, Springer series, 2006

Planned Learning Activities and Teaching Methods

Anlatım Metodu, Ispat Metodu, Tartışma Metodu ve Problem Çözme Metodu

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 * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 3 39 Preparation for midterm exam 1 35 35 Preparation for final exam 1 35 35 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 154

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 LO.1 2 2 2 2 1 2 2 2 LO.2 2 2 2 2 1 2 2 2 LO.3 2 2 2 2 1 2 2 2 LO.4 2 2 2 2 1 2 2 2 LO.5 2 2 2 2 1 2 2 2