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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
YBS 403OPTIMIZATION TECHNIQUES3 + 07th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Compulsory
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
1Knows the fundamental concepts of numerical optimization
2Knows gradient-based unconstrained numerical optimization methods
3Solves related real-world problems by optimization methods
4Modeling 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 001154235422324
LO 002213254232145
LO 003212542335422
LO 004452123541253
Sub Total91211101414141210101314
Contribution233344433334

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)14456
Mid-terms11414
Final examination11818
Total Work Load

ECTS Credit of the Course






130

5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2020-2021 Fall1ATALAY ÇAĞLAR


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
YBS 403 OPTIMIZATION TECHNIQUES 3 + 0 1 Turkish 2020-2021 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Assoc. Prof. Dr. ATALAY ÇAĞLAR acaglar@pau.edu.tr Course location is not specified. %
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 Graphical Method
3 Classical Optimization Methods: Single Variable Optimization
4 Two Variables Optimization
5 Unconstrained Multivariate Optimization Methods: Matrices, Quadratic Form
6 Unconstrained Multivariate Optimization Methods, Gradient Vector, Hessien Matrix
7 Multivariate Optimization Methods with Equality Costraints : Direct Replacement Methods
8 Midterm
9 Multivariate Optimization Methods with Equality Costraints : Lagrange Multipliers Methods
10 Multivariate Optimization Methods with Inequality Costraints: Kuhn-Tucker Conditions
11 Nonlinear Programming (Single Variable Optimization) : Unrestricted Search, Exhaustive Search, Fixed Search
12 Two Symetrical Points Search, Split Search
13 Golden Section Methods, Fibonacci Methods,
14 Gradient Methods: Steepest Ascent Methods, Steepest Descent Methods
Materials
Materials are not specified.
Resources
ResourcesResources Language
Optimizasyon Teknikleri, Hasan Bal, Gazi Üniversitesi, Ankara, 1995.Türkçe
Doğrusal Olmayan Programlama, Gülsüm Oral, Akademi Matbaası, Ankara, 1989.Türkçe
Engineering Optimization: Theory and Practice, Singiresu S. Rao, Wiley Interscience, 1996English
Applied Optimization with MATLAB Programming, P. Venkataraman, Wiley Interscience, NewYork, 2002.English
Optimizasyon, Ayşen Apaydın, A.Ü., Ankara, 2005.Türkçe
Optimizasyon ve Matlab Uygulamaları, Aysun Tezel Özturan, Nobel Akademik Yayıncılık, 1. Baskı, Ankara, 2019Türkçe
Optimizasyon Problemlerinin R İle Çözümü, Namık Kemal Erdoğan, Nisan Kitabevi, Eskişehir, 2016.Türkçe
Nonlinear Programming: Theory and Algorithms, Mokhtar S. Bazaraa Hanif D. Sherali C. M. Shetty, Wiley, Third Edition, 2006.English
Taha, H. A., 1992, Yöneylem Araştırması, (Operations Research: An Introduction, 5th ed. Macmillan, New York.) Literatür, İstanbul, 2000.Türkçe
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