1. FIRST CYCLE - BACHELOR'S DEGREE
  2. FACULTY OF ENGINEERING
  3. COMPUTER ENGINEERING DEPARTMENT
  4. 253 Computer Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
EEEN 479OPTIMIZATION TECHNIQUES3 + 07th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective To teach gradient-based unconstrained numerical optimization techniques. To implement these techniques in MatLab environment. To use these techniques in solving real-world problems.
Course Content One-dimensional nonlinear numerical optimization / Multi-dimensional nonlinear numerical optimization / Mathematical background / Analytical conditions for optimality / First-order methods / Second-order methods / Second-order approximate methods / Applications
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1He/She knows the fundamental concepts of numerical optimization.
2He/She knows gradient-based unconstrained numerical optimization methods.
3He/She can solve related real-world problems by optimization methods.
4He/She can do modeling and prediction by Artificial Neural Networks.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
LO 001 443        
LO 002 555        
LO 0034544        
LO 0045554        
Sub Total9191816        
Contribution255400000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14570
Mid-terms188
Final examination11010
Total Work Load

ECTS Credit of the Course





130

5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2013-2014 Fall3KADİR KAVAKLIOĞLU


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
EEEN 479 OPTIMIZATION TECHNIQUES 3 + 0 3 Turkish 2013-2014 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Prof. Dr. KADİR KAVAKLIOĞLU kadir.kavaklioglu@pau.edu.tr MUH A03107 %70
Goals To teach gradient-based unconstrained numerical optimization techniques. To implement these techniques in MatLab environment. To use these techniques in solving real-world problems.
Content One-dimensional nonlinear numerical optimization / Multi-dimensional nonlinear numerical optimization / Mathematical background / Analytical conditions for optimality / First-order methods / Second-order methods / Second-order approximate methods / Applications
Topics
WeeksTopics
1 Introduction to optimization
2 One dimensional optimization
3 Golden section search
4 Newton and bisection methods
5 Mathematical foundation
6 Gradient descent method
7 Newton Method
8 Conjugate gradient method
9 Review
10 Equality Constraints
11 Inequality Constraints
12 Direct search
13 Simulated annealing
14 Genetic algorithms
Materials
Materials are not specified.
Resources
ResourcesResources Language
Serdar İplikçi Ders NotlarıTürkçe
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam60Final Exam
Midterm Exam40Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes