Ders Planı

Lesson Information

Course Credit
Course ECTS Credit
Teaching Language of Instruction	İngilizce
Level of Course	Bachelor's Degree, TYYÇ: Level 6, EQF-LLL: Level 6, QF-EHEA: First Cycle
Type of Course
Mode of Delivery	Face-to-face
Does the course require compulsory or optional work experience?
Course Coordinator
Instructor (s)
Course Assistant

Purpose and Content

The aim of the course	It is aimed to give the following topics to the students; a) Recognising and classifying an optimisation problem, b) Tools for learning and analysing convex sets and functions, c) Basic algorithms used in solving convex optimisation problems, d) Duality concept in constrained problems and the techniques being used to apply them, mainly staying in the context of convex optimisation, so that they can solve problems which they may encounter with in their studies/projects.
Course Content	Brief reminder of linear algebra topics, Convexity, convex sets and functions, Gradiant Descent, Steepest Descent, Newton Algorithms and their variations for unconstrained problems, Constrained problems and Karush-Kuhn-Tucker Conditions, Modification of the above algorithms for unconstrained problems to constrained problems, İnterior Point Algorithms (Penalty ve Barrier Methods)

The aim of the course

It is aimed to give the following topics to the students; a) Recognising and classifying an optimisation problem, b) Tools for learning and analysing convex sets and functions, c) Basic algorithms used in solving convex optimisation problems, d) Duality concept in constrained problems and the techniques being used to apply them, mainly staying in the context of convex optimisation, so that they can solve problems which they may encounter with in their studies/projects.

Course Content

Brief reminder of linear algebra topics, Convexity, convex sets and functions, Gradiant Descent, Steepest Descent, Newton Algorithms and their variations for unconstrained problems, Constrained problems and Karush-Kuhn-Tucker Conditions, Modification of the above algorithms for unconstrained problems to constrained problems, İnterior Point Algorithms (Penalty ve Barrier Methods)

Learning Outcomes

Mathematics , Science and sufficient knowledge in electrical engineering issues; theoretical and practical knowledge in the field of Electrical and Electronics Engineering the ability to apply for modeling and problem solving.
Ability to identify, define, formulate and solve complex engineering problems; ability to select and implement the appropriate analysis and modeling methods in this respect.
Ability to work effectively in interdisciplinary and multidisciplinary teams; ability to work individually .
Act according to ethical , professional and ethical responsibility about the standards used in electrical and electronic engineering applications
The ability to design to meet specific needs;complex system , process, device or product under realistic constraints and conditions , the ability to apply modern design methods for this purpose .
Awareness of the necessity of lifelong learning ; Access to knowledge, science and developments in technology and continuous self -improvement.
Awareness of universal and social dimensions of health electrical engineering applications , contemporary issues and their impact on the environment and safety ; awareness of the legal consequences of engineering solutions .
Ability to communicate effectively in Turkish, both oral and written, with at least one foreign language knowledge, ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, giving clear and concise instructions and receiving skills.
Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
Analyzing and solving using modern techniques and tools for complex problems encountered in the electrical and electronics application development , selection and use of skills , skills to use ICT effectively
Designing experiments for the study of electrical engineering problems , conduct experiments, collect data , analyze and interpret the results .
Awareness about occupational health and safety
Development and scientific publications of conciousness can be followed in the electrical and electronics engineering. Developed will be able to access the resources that it can meet the education requirements for the new system awareness.

Weekly Course Subjects

1	Brief reminder of linear algebra topics
2	Brief reminder of linear algebra topics
3	Optimality conditions for unconstrained problems Convex Sets
4	Convex and concave functions Conditions for convexity Operations that preserve convexity
5	Quadratic functions, forms and optimization Optimality conditions Unconstrained minimization
6	Descent Methods Convergence
7	Algorithms: Gradient Descent Algorithm
8	Midterm Exam
9	Algorithms: Steepest Descent Algorithm
10	Algorithms: Newton's Algorithm
11	Constrained optimization Duality
12	Optimality conditions, KKT Conditions Algorithms: Feasible Direction Method, Active Set Method
13	Algorithms: Gradient Projection Method, Newton?s Algorithm with Equality Constraints
14	Algorithms: Penalty and Barrier Methods

Resources

1-Luenberger, Linear and Nonlinear Programming, Kluwer, 2002.; 2. Boyd and Vandenberghe, Convex Optimization, Cambridge, 2004.; 3. Baldick, Applied Optimization, Cambridge, 2006.; 4. Freund, Lecture Notes, MIT.; 5. Bertsekas, Lecture Notes, MIT.; 6. Bertsekas, Nonlinear Programming, Athena Scientific, 1999

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Lesson Information

Purpose and Content

Learning Outcomes

Weekly Course Subjects

Resources

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