Module Handbook

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Course MAT-52-16A-K-7

Introduction to Robust Optimization (2V+1U, 4.5 LP)

Course Type

SWS Type Course Form CP (Effort) Presence-Time / Self-Study
- K 4.5 CP 93 h
2 V Lecture 28 h
1 U Exercise class (in small groups) 14 h
(2V+1U) 4.5 CP 42 h 93 h

Basedata

SWS 2V+1U
CP, Effort 4.5 CP = 135 h
Position of the semester 1 Sem. irreg.
Level [7] Master (Advanced)
Language [EN] English
Lecturers
Area of study [MAT-OPT] Optimisation
Additional informations
Livecycle-State [NORM] Active

Notice

This course is a part of the course [MAT-52-16A-K-7].

Contents

The following concepts for robust optimization are presented:
  • Strict robustness,
  • MinMax regret robustness,
  • Adjustable robustness,
  • Recovery robustness,
  • Light robustness.

For these concepts formulations and algorithms for different problem classes (e.g., for linear, non-linear, integer, combinatorial optimization problems) and for different uncertainty sets are developed.

Literature

  • A. Ben-Tal, L. El Ghaoui, A. Nemirovski: Robust Optimization,
  • P. Kouvelis, G. Yu: Robust Discrete Optimization and Its Applications.

Materials

Further literature will be announced in the lecture.

References to Course [MAT-52-16A-K-7]

Module Name Context
[MAT-52-16A-M-7] Introduction to Robust Optimization P: Obligatory 2V+1U, 4.5 LP