GRADUATE SCHOOL

Ph.D. In Electrical-Electronics Engineering

IE 534 | Course Introduction and Application Information

Course Name
Nonlinear Programming
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 534
Fall/Spring
3
0
3
7.5

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
Second Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
Course Coordinator -
Course Lecturer(s) -
Assistant(s) -
Course Objectives The aim of this course is to develop knowledge of different theoretical aspects of nonlinear programming and convex optimization and to give graduate and PhD students the theoretical background on convex analysis and on the theory of optimality conditions, and to provide them with a foundation sufficient to use basic optimization in their own research work and/or to pursue more specialized studies involving optimization theory.
Learning Outcomes The students who succeeded in this course;
  • Will be able to interpret convex sets and convex functions
  • Will be able to analyze extreme points and extreme directions of convex sets
  • Will be able to analyze some topological properties of convex sets and convex functions
  • Will be able to use the concept of convexity in the analysis of nonlinear programming problems
  • Will be able to interpret optimality conditions for nonlinear programming problems
Course Description The course emphasizes the unifying themes such that convex sets and convex functions, their topological properties, separation theorems and optimality conditions for convex optimization problems.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Convex Analysis review and basics
2 Mathematical Preliminaries
3 Mathematical Preliminaries
4 Nonlinear Optimization: Line searches
5 Nonlinear Optimization: Line searches
6 Unconstrained Problems
7 Unconstrained Problems
8 Midterm
9 Constrained Problems
10 Constrained Problems
11 Linearly Constrained Problems
12 Lagrangian Duality
13 Paper Presentations
14 Review and Project Presentations
15 -
16 Final

 

Course Notes/Textbooks Nonlinear Programming. Theory and Algorithms., Mokhtar S. Bazaraa, Hanif D. Sherali, C.M. Shetty, John Wiley & Sons, ISBN 0471557935.
Suggested Readings/Materials Bertsekas, D. Nonlinear Programming, Second Edition, Athena Scientific Publishing, 1999.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
1
10
Portfolio
Homework / Assignments
1
10
Presentation / Jury
Project
1
25
Seminar / Workshop
Oral Exams
Midterm
1
25
Final Exam
1
30
Total

Weighting of Semester Activities on the Final Grade
4
70
Weighting of End-of-Semester Activities on the Final Grade
1
30
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
14
8
112
Field Work
0
Quizzes / Studio Critiques
1
0
Portfolio
0
Homework / Assignments
4
6
24
Presentation / Jury
6
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
10
10
Final Exam
1
15
15
    Total
209

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1 Accesses information in breadth and depth by conducting scientific research in Electrical and Electronics Engineering; evaluates, interprets and applies information.
2 Is well-informed about contemporary techniques and methods used in Electrical and Electronics Engineering and their limitations.
3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines. Knows and applies the research methods in studies of the area with a high level of skill.
4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
5 Defines and formulates problems related to Electrical and Electronics Engineering, develops methods to solve them and uses progressive methods in solutions. Can independently realize novel studies that bring innovation to the field, or methods, or design, or known methods.
6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.
7 Designs and implements studies based on theory, experiments and modeling; analyses and resolves the complex problems that arise in this process. Performs critical analysis, synthesis and evaluation of new and complex ideas.
8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility.
9 Engages in written and oral communication at least in Level C1 of the European Language Portfolio Global Scale.
10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
11 Evaluates the results of scientific, technological and engineering research and development activities in terms of the social, environmental, health, safety and legal aspects. Examines social relations and norms related to the field, and develops and makes attempts to change them if necessary. Knows their project management and business applications, and is aware of their limitations in Electrical and Electronics Engineering applications.
12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. Adheres to the principles of research and publication ethics.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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