- modelling with robust optimization,
- modelling and concepts of uncertainty set,
- model reformulations in solvable problems.
- problem complexities,
- linear, non-linear and integer optimization in robust optimization,
- application to combinational problems,
- approaches from robust optimization: Soyster approach for uncertain problems; strict robustness; robust regularization; minimax regret approach; adjustable robustness; approach by Bertsimas and Sim; recoverable robustness.
Robust Optimization (M, 9.0 LP)
|Module Number||Module Name||CP (Effort)|
|MAT-52-16-M-7||Robust Optimization||9.0 CP (270 h)|
|CP, Effort||9.0 CP = 270 h|
|Position of the semester||1 Sem. irreg.|
|Level|| Master (Advanced)|
|Area of study||[MAT-OPT] Optimisation|
|Reference course of study||[MAT-88.105-SG] M.Sc. Mathematics|
|Type/SWS||Course Number||Title||Choice in |
|SL||SL is |
required for exa.
|P||84 h||186 h||-||-||PL1||9.0||irreg.|
- About [MAT-52-16-K-7]: Title: "Robust Optimization"; Presence-Time: 84 h; Self-Study: 186 h
Examination achievement PL1
- Form of examination: oral examination (20-30 Min.)
- Examination Frequency: irregular (by arrangement)
- Examination number: 86387 ("Robust Optimization")
Evaluation of grades
The grade of the module examination is also the module grade.
Competencies / intended learning achievements
In the exercise classes, the students have deepened their knowledge and gained a skilled, precise and independent handling of the terms, propositions and methods taught in the lecture. Moreover, they have learned to apply algorithms and models to practical problems by the use of appropriate, higher programming languages and MIP solvers.
- A. Ben-Tal, L. El Ghaoui, A. Nemirovski: Robust Optimization,
- P. Kouvelis, G. Yu: Robust Discrete Optimization and Its Applications.
Requirements for attendance of the module (informal)
- [MAT-10-1-M-2] Fundamentals of Mathematics (M, 28.0 LP)
- [MAT-14-13-M-3] Linear and Network Programming (M, 9.0 LP)
- [MAT-50-11-M-4] Integer Programming: Polyhedral Theory and Algorithms (M, 9.0 LP)