Universität Wien

040968 UK Graph Algorithms and Network Flows (2015S)

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

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).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 17.03. 18:30 - 20:00 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 16.04. 11:30 - 13:00 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 16.04. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 17.04. 11:30 - 13:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 27.04. 11:30 - 13:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 28.04. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 28.04. 18:30 - 20:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 30.04. 11:30 - 13:00 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 30.04. 13:15 - 14:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 09.06. 16:45 - 18:30 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 09.06. 18:30 - 21:00 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 16.06. 16:45 - 21:00 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 23.06. 18:30 - 20:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 06.07. 15:00 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock

Information

Aims, contents and method of the course

Networks are apparent in our daily lives. Typical examples of networks are:
electrical and power networks, telephone or Internet data networks, traffic net-
works (highways, rail networks, airline service networks), manufacturing and
distribution networks, or even social networks.
Graphs are used to model networks, and the underlying optimization problems are solved by means of graph algorithms.

Assessment and permitted materials

Minimum requirements and assessment criteria

This course should help graduate students to:
a) understand information about networks, and
b) develop mathematical models and algorithms to design networks.
In particular the main aims of the course are to:
- provide the knowledge of the fundamental concepts of networks
- provide the knowledge of the fundamental concepts of integer programming
- learn skills in mathematical modeling of optimization problems on networks
- learn skills in developing algorithmic techniques.

Examination topics

Reading list

Association in the course directory

Last modified: Mo 07.09.2020 15:29