EEE5010 OptimizationBahçeşehir UniversityDegree Programs ELECTRIC-ELECTRONIC ENGINEERING (ENGLISH, NON-THESIS)General Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ELECTRIC-ELECTRONIC ENGINEERING (ENGLISH, NON-THESIS)
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
EEE5010 Optimization Spring 3 0 3 9
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Prof. Dr. SÜREYYA AKYÜZ
Course Lecturer(s): Prof. Dr. SÜREYYA AKYÜZ
Recommended Optional Program Components: None
Course Objectives: To equip students with the mathematical theory of optimization and solution methods.

Learning Outcomes

The students who have succeeded in this course;
Students will
- be able to formulate optimization problems
- understand basic differences between various constraints
- apply numerical techniques to solve optimization problems

Course Content

Optimization as a decision making problem. Optimization over an open set. Optimization under equality constraints; Lagrange multipliers. Optimization under inequality constraints. Linear programming. Numerical methods.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) The Optimization Problem. Examples.
2) Mathematical preliminaries
3) Mathematical preliminaries
4) The Weierstrass Theorem. Application to example problems.
5) Optimization over an open set. Necessary and sufficient conditions.
6) Numerical techniques: Gradient algorithm, Newton's method.
8) Optimization with equality constraints. Lagrange multipliers.
9) Optimization with inequality constraints. Kuhn-Tucker conditions.
10) Linear programming: Standard maximization and minimization problems.
11) Linear programming: Primal and dual problems. Duality theorem. Optimality conditions.
12) The Simplex algorithm.
13) Discrete dynamic programming.
14) Large optimization problems. Decomposition methods.

Sources

Course Notes / Textbooks: 1. P. Varaia, Lecture Notes on Optimization, web
References: 1. C.T. Kelley, Iterative Methods for Optimization, SIAM

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Homework Assignments 5 % 25
Midterms 1 % 25
Final 1 % 50
Total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
Total % 100

ECTS / Workload Table

Activities Number of Activities Workload
Course Hours 14 42
Study Hours Out of Class 16 136
Homework Assignments 5 10
Midterms 1 2
Final 1 2
Total Workload 192

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Have sufficient background and an ability to apply knowledge of mathematics, science, and engineering to identify, formulate, and solve problems of electrical and electronics engineering.
2) Be able to define, formulate and solve sophisticated engineering problems by choosing and applying appropriate analysis and modeling techniques and using technical symbols and drawings of electrical and electronics engineering for design, application and communication effectively.
3) Have an ability to design or implement an existing design of a system, component, or process to meet desired needs within realistic constraints (realistic constraints may include economic, environmental, social, political, health and safety, manufacturability, and sustainability issues depending on the nature of the specific design).
4) Elektrik ve elektronik mühendisliği yapabilmek ve yeni uygulamalara uyum gösterebilmek için gerekli yenilikçi ve güncel teknikler, beceriler, bilgi teknolojileri ve modern mühendislik araçlarını geliştirmek, seçmek, uyarlamak ve kullanmak.
5) Be able to design and conduct experiments, as well as to collect, analyze, and interpret relevant data, and use this information to improve designs.
6) Be able to function individually as well as to collaborate with others in multidisciplinary teams.
7) Be able to communicate effectively in English and Turkish (if he/she is a Turkish citizen).
8) Be able to recognize the need for, and to engage in life-long learning as well as a capacity to adapt to changes in the technological environment.
9) Have a consciousness of professional and ethical responsibilities as well as workers’ health, environment and work safety.
10) Have the knowledge of business practices such as project, risk, management and an awareness of entrepreneurship, innovativeness, and sustainable development.
11) Have the broad knowledge necessary to understand the impact of electrical and electronics engineering solutions in a global, economic, environmental, legal, and societal context.