This course concerns numerical methods for optimization. It is part of the Bachelor of Science program of the Automation Department, UTCluj (4th year 2nd semester). As prerequisites, knowledge of analysis and linear algebra is needed, together with notions of Matlab programming. The responsible lecturer is Zsófia Lendek.
Grading:
- 60% partial exam
- 40% final exam.
Schedule
Below the schedule, including the partial exam.
The lectures will be taught online, on Microsoft Teams. If you have not been included in the team, please contact the course responsible. The lecture notes are available below:
- Chapter 1: Analytical methods.
- Chapter 2: Numerical optimization.
- Chapter 3: Linear programming.
- Chapter 4: Quadratic programming.
- Chapter 5: Genetic algorithms and some kangaroos.
- Appendix: Matrix differentiation.
Practical classes
In the practical classes, a set of assignments must be solved. You may work in groups of at most 2. An exercises is completed when the method is implemented and the corresponding problem is solved. For a (very) short introduction of the algorithms to be used and examples, see the lab guide. The Matlab files corresponding to the first lab session are available here.
The exercises you have to solve are those corresponding to the labs, given in situation. If you do not have an exercise scheduled, please contact the TA. The requirements for the labs are as follows:
- Function approximation
- Analytical methods
- Elimination methods
- Newton and gradient
- Conjugate gradient
- Quasi-Newton
- Nelder-Mead
- Rosenbrock
- Simplex
- Active set
Contact
Comments, suggestions, questions etc. related to this course or website are welcome; please contact the lecturer.