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COURSE UNIT TITLECOURSE UNIT CODESEMESTERTHEORY + PRACTICE (Hour)ECTS
OPTIMIZASYON II EEM619 - 3 + 0 10

TYPE OF COURSE UNITElective Course
LEVEL OF COURSE UNITDoctorate Of Science
YEAR OF STUDY-
SEMESTER-
NUMBER OF ECTS CREDITS ALLOCATED10
NAME OF LECTURER(S)Professor Sedat Nazlıbilek
LEARNING OUTCOMES OF THE COURSE UNIT At the end of this course, the students;
1) Gain an ability to solve problems.
2) Know the Variational Analysis and use them.
3) Know the theory and applications of Concavity Theory.
4) Will be able to calculate Cost functions.
5) Know and use Dynamic Programing applications.
6) Know and improve the Linear/Quadratic Programing applications.
7) Experience the theoretical knowledge with simulations.
MODE OF DELIVERYFace to face
PRE-REQUISITES OF THE COURSENo
RECOMMENDED OPTIONAL PROGRAMME COMPONENTNone
COURSE DEFINITIONCalculus of variations and pontryagin's principle. Variational approach applications. Dynamic optimization with or without constraints. Dynamic programming (Hamilton-Jacobi-Bellman). Convex optimization basics. Linear and quadratic programming.
COURSE CONTENTS
WEEKTOPICS
1st Week Calculus of Variations
2nd Week Calculus of Variations - Pontryagin's principle
3rd Week Applications of Variational Approach
4th Week Applications of Variational Approach
5th Week Dynamic Optimization
6th Week Dynamic Optimization
7th Week Midterm Exam
8th Week Dynamic Programming - Principle of Optimality
9th Week Dynamic Programming - Hamilton-Jacobi-Bellman equation
10th Week Dynamic Programming - Applications
11th Week Convex Optimization Basics
12th Week Linear Programming
13th Week Quadratic Programming
14th Week Presentations (HJB, LQR, Two-point BVP, Network Optimization, Games etc.)
RECOMENDED OR REQUIRED READING1.E.Polak, OPTIMIZATION, Algorithms and Consistent Approximations, Springer, 1997
2.A.E. Bryson, Dynamic Optimization, Addison, 1999.
3.E. Kirk, Optimal Control Theory, Prentice Hall, 1970.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODSLecture,Questions/Answers
ASSESSMENT METHODS AND CRITERIA
 QuantityPercentage(%)
Mid-term130
Assignment110
Project115
Attendance15
Total(%)60
Contribution of In-term Studies to Overall Grade(%)60
Contribution of Final Examination to Overall Grade(%)40
Total(%)100
ECTS WORKLOAD
Activities Number Hours Workload
Midterm exam133
Preparation for Quiz000
Individual or group work148112
Preparation for Final exam14040
Course hours14342
Preparation for Midterm exam13030
Laboratory (including preparation)000
Final exam133
Homework23570
Total Workload300
Total Workload / 3010
ECTS Credits of the Course10
LANGUAGE OF INSTRUCTIONTurkish
WORK PLACEMENT(S)No
  

KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
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