Universität Wien

040968 UK Graph Algorithms and Network Flows (MA) (2019S)

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

The course is slightly blocked which means that from March to May we will do four units in a row (instead of two units), while in June we have no units at all.
Note that the four units on one day will usually take place in two different rooms.

  • Tuesday 05.03. 11:30 - 13:00 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 05.03. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 19.03. 11:30 - 13:00 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 19.03. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 26.03. 11:30 - 13:00 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 26.03. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 02.04. 11:30 - 13:00 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 02.04. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 09.04. 11:30 - 13:00 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 09.04. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 30.04. 11:30 - 13:00 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 30.04. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 07.05. 11:30 - 13:00 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 14.05. 11:30 - 13:00 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 14.05. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 21.05. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Aims, contents and method of the course

Networks are apparent in our daily lives. Typical examples are: electrical and power networks, data networks, traffic networks (streets, rails, airline routes), manufacturing and distribution networks, and (online) social networks.
Graphs are used to model these networks in an abstract way and allow to efficiently solve problems on networks by using standardized graph algorithms.
In detail we discuss:
- matchings (stable marriage problem)
- computational complexity
- graph connectivity and search algorithms
- maximum flows
Furthermore, we consider tools and algorithms for (social) network analysis:
- community detection
- partitioning and clustering
- strong and weak ties
- positive and negative relationships

The goals of this course are to:
- understand the fundamental concepts of networks
- understand basic graph algorithms
- be able to apply algorithms to network based problems
- be able to analyze networks based on different measures

The methods for knowledge transfer and gain are:
- lectures
- student presentations of selected topics
- joint discussions of exercises and according solutions
- practical implementation of algorithms

Assessment and permitted materials

Students collect points with the following actions:
- exercise presentations: students present their solutions to given exercises on the blackboard (max. 10 points)
- topic presentations: students present a selected topic in front of the class (max. 20 points)
- programming exercise: students implement a selected algorithm (max. 20 points)
- written exam: no supporting material allowed (max. 60 points)

Minimum requirements and assessment criteria

- Attendance at the lecture / exercise / presentation units is NOT required.
- The grade is determined by the total number of points collected:
1: 89+
2: 76 - 88
3: 63 - 75
4: 50 - 62
5: 0 - 49
- There is NO minimal required number of points for each action.

Examination topics

For the final written exam you have to know:
- the contents of the lecture slides
- the solutions to the blackboard exercises

Reading list

- T.H. Cormen, C.E. Leiserson, R.L. Rivest, Introduction to Algorithms, MIT Press, 1990
- D. Jungnickel: Graphen, Netzwerke und Algorithmen, BI Wissenschaftsverlag, 3. Auflage, 1994
- J. Bang-Jensen, G. Gutin: Digraphs: Theory, Algorithms and Applications, Springer, 2001
- R.K. Ahuja, T.L. Magnanti, J.B. Orlin, Network Flows: Theory, Algorithms, and Applications, Prentice Hall, 1993
- D. Easley, J. Kleinberg, Networks, Crowds, and Markets: Reasoning About a Highly Connected World, Cambridge University Press, 2010
- E. Tardos, J. Kleinberg, Algorithm Design, Addison Wesley, 2005

Association in the course directory

Last modified: Mo 07.09.2020 15:29