EEE5010 OptimizationBahçeşehir UniversityDegree Programs ELECTRICAL AND ELECTRONICS ENGINEERINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ELECTRICAL AND ELECTRONICS ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
EEE5010 Optimization Fall 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: Bachelor’s Degree (First Cycle)
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) Adequate knowledge in mathematics, science and electric-electronic engineering subjects; ability to use theoretical and applied information in these areas to model and solve engineering problems. 4
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. 4
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.) 3
4) Ability to devise, select, and use modern techniques and tools needed for electrical-electronic engineering practice; ability to employ information technologies effectively. 3
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing.
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9) Awareness of professional and ethical responsibility.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.