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OFTF
OF FACULTY of TECHNOLOGY / DEPARTMENT of ELECTRONICS and COMMUNICATION ENGINEERING /
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EHM2012Optimization Theory and Applications2+0+0ECTS:4
Year / SemesterSpring Semester
Level of CourseFirst Cycle
Status Elective
DepartmentDEPARTMENT of ELECTRONICS and COMMUNICATION ENGINEERING
Prerequisites and co-requisitesNone
Mode of Delivery
Contact Hours14 weeks - 2 hours of lectures per week
LecturerDr. Öğr. Üyesi Emin TUĞCU
Co-Lecturer
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
To gain the ability to use basic mathematical and physics principles in optimum design of engineering systems, to make a logical and systematic approach for optimum solution of engineering problems.
 
Learning OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
LO - 1 : Knows the basic concepts of optimization1,2,3,41,
LO - 2 : Knows derivative-based unconstrained numerical optimization methods1,2,3,41,
LO - 3 : Can solve real world problems with optimization methods1,2,3,41,
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome

 
Contents of the Course
What is optimization, What are its applications in engineering, Definition and classification of optimization problem, Graphical optimization, Classical optimization techniques Univariate optimization , Unconstrained multivariate optimization, Equation constrained multivariate optimization , Nonlinear programming, One dimensional unconstrained optimization Geometric programming, Unconstrained geometric programming problems, Geometric programming, Constrained geometric programming problems, Linear programming
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Introduction to Optimization, What is Optimization. What are its applications in engineering
 Week 2Definition and classification of the optimization problem
 Week 3Graphical optimization
 Week 4Classical Optimization Methods: Univariate Optimization
 Week 5Bivariate Optimization
 Week 6Unconstrained Multivariate Optimization: Matrices, Quadratic Format
 Week 7Unconstrained Multivariate Optimization, Gradient Vector, Hessien Matrix
 Week 8Equality Constrained Multivariate Optimization: Direct Substitution Method
 Week 9Midterm
 Week 10Equality Constrained Multivariate Optimization: Lagrange Multipliers Method
 Week 11Inequality Constrained Multivariate Optimization: Kuhn-Tucker Conditions
 Week 12Non-Linear Programming (Single Variable Optimization Methods): Unconstrained Search, Exact Search, Constant Search
 Week 13Two-Symmetric Point Search, Three-Division Search
 Week 14Gradient Methods: Fastest Ascent Method, Fastest Descend Method
 Week 15Linear programming
 Week 16End-of-term exam
 
Textbook / Material
1Optimizasyon ve Matlab Uygulamaları , Aysun Tezel Özturan, Nobel Akademik Yayıncılık,978-6057846266, 2019.
 
Recommended Reading
1Engineering Optimization and Application, ,Singiresu S. Rao, , ,Wiley Eastern Limited,,0-4714555034-5,Kanada,1996
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 2 50
End-of-term exam 16 2 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 2 14 28
Sınıf dışı çalışma 2 14 28
Arasınav için hazırlık 3 8 24
Arasınav 2 1 2
Dönem sonu sınavı için hazırlık 2 15 30
Dönem sonu sınavı 2 1 2
Total work load114