| 1. | Course Title | Convex Optimization with Applications | |||||||||||
| 2. | Code | 4ФЕИТ11003 | |||||||||||
| 3. | Study program | 11-IBS, 12-KIT, 13-PMA, 21-PNMI | |||||||||||
| 4. | Organizer of the study program (unit, institute, department) | Faculty of Electrical Engineering and Information Technologies | |||||||||||
| 5. | Degree (first, second, third cycle) | Second cycle | |||||||||||
| 6. | Academic year/semester | I/1 | 7. | Number of ECTS credits | 6.00 | ||||||||
| 8. | Lecturer | Dr Katerina Hadzi-Velkova Saneva, Dr Zoran Hadji-Velkov | |||||||||||
| 9. | Course Prerequisites | ||||||||||||
| 10. | Course Goals (acquired competencies):
Understanding the theory of convex optimization. Ability to recognize, model and solve optimization problems in engineering. |
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| 11. | Course Syllabus:
Introduction to mathematical optimization. Convex sets. Convex functions. Operations that preserve convexity. Linear programming. Quadratic programming. Semidefinite programming. Lagrange duality. Optimality conditions. Methods for solving constrained and unconstrained convex problems. Software tools for convex optimization problems. Recognition and modeling of convex optimization problems in engineering. |
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| 12. | Learning methods:
Lectures, seminar papers, project and independent assignments, self study. |
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| 13. | Total number of course hours | 180 | |||||||||||
| 14. | Distribution of course hours | 3 + 3 | |||||||||||
| 15. | Forms of teaching | 15.1 | Lectures-theoretical teaching | 45 hours | |||||||||
| 15.2 | Exercises (laboratory, practice classes), seminars, teamwork | 0 hours | |||||||||||
| 16. | Other course activities | 16.1 | Projects, seminar papers | 45 hours | |||||||||
| 16.2 | Individual tasks | 45 hours | |||||||||||
| 16.3 | Homework and self-learning | 45 hours | |||||||||||
| 17. | Grading | ||||||||||||
| 17.1 | Exams | 0 points | |||||||||||
| 17.2 | Seminar work/project (presentation: written and oral) | 50 points | |||||||||||
| 17.3. | Activity and participation | 0 points | |||||||||||
| 17.4. | Final exam | 50 points | |||||||||||
| 18. | Grading criteria (points) | up to 50 points | 5 (five) (F) | ||||||||||
| from 51 to 60 points | 6 (six) (E) | ||||||||||||
| from 61 to 70 points | 7 (seven) (D) | ||||||||||||
| from 71 to 80 points | 8 (eight) (C) | ||||||||||||
| from 81 to 90 points | 9 (nine) (B) | ||||||||||||
| from 91 to 100 points | 10 (ten) (A) | ||||||||||||
| 19. | Conditions for acquiring teacher’s signature and for taking final exam | Regular attendance of classes / consultations | |||||||||||
| 20. | Forms of assessment | Preparation and presentation of a seminar paper / project assignment; written exam. The written exam has a maximum duration of 120 minutes, during which the use of books, scripts, manuscripts or notes is allowed. | |||||||||||
| 21. | Language | Macedonian and English | |||||||||||
| 22. | Method of monitoring of teaching quality | Self-evaluation | |||||||||||
| 23. | Literature | ||||||||||||
| 23.1. | Required Literature | ||||||||||||
| No. | Author | Title | Publisher | Year | |||||||||
| 1. | S. Boyd and L. Vandenberghe | Convex Optimization | Cambridge University Press | 2004 | |||||||||
| 2. | D.G. Luenberger и Y. Ye | Linear and Nonlinear Programming | Springer | 2016 | |||||||||
| 23.2. | Additional Literature | ||||||||||||
| No. | Author | Title | Publisher | Year | |||||||||
| 1. | P. Venkataram | Applied Optimization with MATLAB Programming | John Wiley and Sons | 2009 | |||||||||
