Course Details

NONLINEAR PROGRAMMING

IE416

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Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
1IE416NONLINEAR PROGRAMMING3+0+035

Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program INDUSTRIAL ENGINEERING
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course • To provide students with a solid foundation in nonlinear optimization theory and methods.
• To develop students' skills in formulating and solving real-world optimization problems.
• To enhance students' analytical and computational skills in the context of optimization.
Course Content This course focuses on the theory and algorithms for nonlinear optimization problems. It covers unconstrained and constrained optimization, convex optimization, and introduces students to various optimization algorithms and their applications in engineering and decision-making processes.
Course Methods and Techniques This course will be offered in Class format. We will be using various tools for active learning to take place. This is also a student-driven course. It is your responsibility to participate actively in class discussions. You are not graded on whether you agree or disagree with the instructor or with each other. Evaluation of class participation will be based on your ability to raise and answer important issues, to contribute ideas or insights, to build upon the ideas of others, ask questions to presenters, etc.
Prerequisites and co-requisities None
Course Coordinator Associate Prof.Dr. Ramazan Ünlü
Name of Lecturers Associate Prof.Dr. Ramazan Ünlü
Assistants Associate Prof.Dr. Ramazan Ünlü
Work Placement(s) No

Recommended or Required Reading
Resources Nocedal, J., & Wright, S. (2006). Numerical optimization. Springer Science & Business Media.
On Canvas
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Course Category
Engineering %100

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Quiz/Küçük Sınav 1 % 25
Ödev 4 % 20
Proje/Çizim 1 % 20
Final examination 1 % 30
Diğer (Staj vb.) 1 % 5
Total
8
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Grup Projesi 30 1 30
Sınıf İçi Aktivitesi 14 2,5 35
Okuma 14 2 28
Kişisel Çalışma 14 2 28
Ders dışı çalışma 20 1 20
Total Work Load   Number of ECTS Credits 5 141

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Explain the fundamental concepts and theories of nonlinear optimization
2 Formulate real-world problems as nonlinear optimization models.
3 Apply appropriate algorithms to solve unconstrained and constrained nonlinear optimization problems.
4 Analyze the convergence properties and computational complexity of nonlinear optimization algorithms.
5 Evaluate the effectiveness of different optimization techniques for various problem types.
6 Develop optimization models and implement solution algorithms using appropriate software tools.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to Nonlinear Optimization
2 Unconstrained Optimization
3 Unconstrained Optimization
4 Line Search Methods
5 Trust Region Methods
6 Conjugate Gradient Methods
7 Quasi-Newton Methods
8 Break
9 Midterm Exam
10 Constrained Optimization
11 Penalty and Barrier Methods
12 Sequential Quadratic Programming
13 Interior Point Methods
14 Convex Optimization
15 Applications and Project Presentations


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
C1 4 3
C2 4 5 3 2
C3 5 5 4 4
C4 5 4 3
C5 4 5 3 3
C6 4 5 4 5 2 2

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=72424&lang=en
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