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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 5091 INTRODUCTION TO OPTIMIZATION ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR MURAT TANIK

Offered to

Econometrics

Course Objective

This course covers the mathematical building blocks of optimization algorithms, and modeling and solution of optimization problems by various optimization algorithms.

Learning Outcomes of the Course Unit

1   To be able to understand the basic principles of optimization. 2   To be able to generate problem as an optimization problem. 3   To be able to determine the objective function and constraints of a problem. 4   To be able to understand the selection criteria of an optimization algorithm. 5   To be able to solve an optimization problem analitically.

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 theory 2 Convexity 3 Concepts and calculations of directional derivative, Jacobien and Hessian matrices 4 Optimality conditions 5 Modelling 6 Applications of modelling 7 Article reviews 8 Mid-term 9 Unconstrained optimization algorithms 10 Applications of Unconstrained optimization 11 Constrained optimization algorithms 12 Applications of constrained optimization 13 Article reviews 14 Article reviews

Recomended or Required Reading

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

Planned Learning Activities and Teaching Methods

This course will be presented using class lectures, class discussions, overhead projections, and demonstrations.

Assessment Methods

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

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 2 26 Preparation for midterm exam 1 20 20 Preparation for final exam 1 20 20 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 111

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 LO.1 2 2 2 2 2 2 2 2 LO.2 2 2 2 2 2 2 2 2 LO.3 2 2 2 2 2 2 2 2 LO.4 2 2 2 2 2 2 2 2 LO.5 2 2 2 2 2 2 2 2