Universität Wien FIND

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040114 UK Optimization under Uncertainty (MA) (2019S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

Registration/Deregistration

Details

max. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Monday 04.03. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 11.03. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 18.03. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 25.03. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 01.04. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 08.04. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 29.04. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 06.05. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 13.05. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 20.05. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 27.05. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 03.06. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 17.06. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 24.06. 08:00 - 09:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß

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)

The main themes are discussed first in form of a lecture. Homeworks then give the opportunity to apply and deepen the teaching material.

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

The test measures the ability to solve simple examples in the dicussed fields.

Examination topics

1) Single stage stochastic optmiization, in particular mean-variance optimization, expected utility, acceptability measures
2) Decision trees
3) Markov chains
4) Markov decision processes

Reading list

Hillier/Lieberman, Introduction to Operations Research, 7th edition, 2017

Association in the course directory

Last modified: Mo 07.09.2020 15:28