COURSE UNIT TITLE

: APPLIED OPTIMIZATION

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EMT 3022 APPLIED OPTIMIZATION ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR GÖKÇE BAYSAL TÜRKÖLMEZ

Offered to

Econometrics
Econometrics (Evening)

Course Objective

The main objective of the course is to analyze solution methods of nonlinear optimization models in real world problems and computer applications. Theoretical information about optimization methods will be applied to economics and business problems by using Matlab programming language. The lecture will be held in computer laboratory.

Learning Outcomes of the Course Unit

1   To be able to classify optimization probems.
2   To be able to set optimization models of economics and business problems.
3   To be able to apply solution methods of optimization problems.
4   To be able to solve problems by using Matlab programming.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Essential Concepts of Optimization
2 Introduction to Unconstrained Optimization
3 Convex Sets and Convex Functions
4 Introduction to Matlab Programming Language
5 Gradient and Directional Derivative and Applications
6 Solution Methods of Unconstrained Optimization 1: Newton s Method
7 Matlab Applications
8 Mid-term
9 Mid-term
10 Solution Methods of Unconstrained Optimization 2: Steepest Descent Method
11 Equality Constrained Optimization: Lagrange Theory
12 Economics Applications
13 Matlab Applications
14 Matlab Applications

Recomended or Required Reading

1- Peressini A.L., Sullivan F.E., Uhl, Jr.J.J.; The Mathematics of Nonlinear Programming, Springer-Verlag, 1991.
2- Sundaram R. K.; A First Course in Optimization Theory, Cambridge University Press, 2009
3-Deveci Kocakoç I.; Matlab ve Istatistiksel Veri Analizi, 3. Basım, Nobel Akademik Yayıncılık, 2010

Planned Learning Activities and Teaching Methods

The lecture will be held in computer laboratory. This course will be presented using class lectures, class discussions, overhead projections, and demonstrations

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 MTEG MIDTERM GRADE MTEG * 1
3 FIN FINAL EXAM
4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60


*** 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 12 3 36
Preparations before/after weekly lectures 12 2 24
Preparation for midterm exam 1 25 25
Preparation for final exam 1 28 28
Midterm 1 1 1
Final 1 1 1
TOTAL WORKLOAD (hours) 115

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.14
LO.224
LO.324
LO.45

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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