040114 UK Optimization under Uncertainty (MA) (2018S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from We 14.02.2018 09:00 to We 21.02.2018 12:00
- Deregistration possible until We 14.03.2018 23:59
Details
max. 50 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Monday 05.03. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Wednesday 07.03. 09:45 - 11:15 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
- Wednesday 14.03. 09:45 - 11:15 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 19.03. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 09.04. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 16.04. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 23.04. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 30.04. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Wednesday 02.05. 09:45 - 11:15 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
- Monday 07.05. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Wednesday 09.05. 09:45 - 11:15 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 14.05. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 28.05. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 04.06. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 11.06. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 18.06. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Monday 25.06. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Information
Aims, contents and method of the course
Study practically relevant aspects of operations research including in particular the consideration of uncertain input data (stochastic optimization, robust optimization)
Assessment and permitted materials
written exam, blackboard exercises
Minimum requirements and assessment criteria
This course should help graduate students to:
a) develop mathematical models for (real world) optimization problems
b) apply different concepts to treat uncertain input data in optimization and understand the consequences implied by choosing on of these techniques
a) develop mathematical models for (real world) optimization problems
b) apply different concepts to treat uncertain input data in optimization and understand the consequences implied by choosing on of these techniques
Examination topics
Reading list
Association in the course directory
Last modified: Mo 07.09.2020 15:28