| TYPE OF COURSE UNIT | Elective Course |
| LEVEL OF COURSE UNIT | Master's Degree With Thesis |
| YEAR OF STUDY | - |
| SEMESTER | - |
| NUMBER OF ECTS CREDITS ALLOCATED | 10 |
| NAME OF LECTURER(S) | . Servıs Servıs
|
| LEARNING OUTCOMES OF THE COURSE UNIT |
At the end of this course, the students;
1) are provided with a comprehensive and advanced understanding of the deterministic and stochastic dynamic programming in an advanced way and demonstrate some applied optimization and modeling.
2) are provided with modeling skills in solving practical cases.
|
| MODE OF DELIVERY | Face to face |
| PRE-REQUISITES OF THE COURSE | No |
| RECOMMENDED OPTIONAL PROGRAMME COMPONENT | None |
| COURSE DEFINITION | This course focuses on the mathematical ideas and computational methods used in the optimization theory. |
| COURSE CONTENTS | | WEEK | TOPICS |
|---|
| 1st Week | Dynamic systems: local and global analysis | | 2nd Week | Dynamic systems: local and global analysis | | 3rd Week | Dynamic systems: local and global analysis | | 4th Week | Deterministic dynamic programming: theory and numerical implementation | | 5th Week | Deterministic dynamic programming: theory and numerical implementation | | 6th Week | Deterministic dynamic programming: theory and numerical implementation | | 7th Week | Stochastic dynamic programming: theory and numerical implementation | | 8th Week | Midterm | | 9th Week | Stochastic dynamic programming: theory and numerical implementation | | 10th Week | Markov processes: weak and strong convergence | | 11th Week | Markov processes: weak and strong convergence | | 12th Week | Markov processes: weak and strong convergence | | 13th Week | Markov processes: weak and strong convergence | | 14th Week | Markov processes: weak and strong convergence |
|
| RECOMENDED OR REQUIRED READING | J. Lundgren, M. Rönnqvist, and P. Varbrand, Optimization, Studentlitteratur, 2010.
M. Henningsson, J. Lundgren, M. Rönnqvist, and P. Varbrand, Optimization, Studentlitteratur, 2010. |
| PLANNED LEARNING ACTIVITIES AND TEACHING METHODS | Lecture,Discussion |
| ASSESSMENT METHODS AND CRITERIA | | | Quantity | Percentage(%) |
|---|
| Mid-term | 1 | 40 | | Quiz | 1 | 10 | | Total(%) | | 50 | | Contribution of In-term Studies to Overall Grade(%) | | 50 | | Contribution of Final Examination to Overall Grade(%) | | 50 | | Total(%) | | 100 |
|
| ECTS WORKLOAD |
| Activities |
Number |
Hours |
Workload |
| Midterm exam | 1 | 2 | 2 | | Preparation for Quiz | 1 | 55 | 55 | | Individual or group work | 14 | 5 | 70 | | Preparation for Final exam | 1 | 70 | 70 | | Course hours | 14 | 3 | 42 | | Preparation for Midterm exam | 1 | 60 | 60 | | Laboratory (including preparation) | | | | | Final exam | 1 | 2 | 2 | | Homework | | | | | Total Workload | | | 301 |
|---|
| Total Workload / 30 | | | 10,03 |
|---|
| ECTS Credits of the Course | | | 10 |
|---|
|
| LANGUAGE OF INSTRUCTION | Turkish |
| WORK PLACEMENT(S) | No |
| | |
