Universität Wien

040968 UK Graph Algorithms and Network Flows (MA) (2020S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Actions due to the current situation:
- Lectures will be recorded and uploaded in Moodle.
- Course material (slides, descriptions, etc.) will be anyway in Moodle.
- Solutions to homework and programming exercises have to be uploaded to Moodle until the corresponding deadlines.
- The final exam will be online in Moodle on June 23, 13-15h:
* at start time the exam can be downloaded as PDF
* you can solve the exercises electronically or on paper, using any resources (open book)
* you upload your solutions as single PDF (including electronic documents, scans, photos) until the end time

  • Dienstag 03.03. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 10.03. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Montag 16.03. 13:15 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 17.03. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Donnerstag 19.03. 09:45 - 11:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Donnerstag 19.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 24.03. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 31.03. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 21.04. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 28.04. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 05.05. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 12.05. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 19.05. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 26.05. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 09.06. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 16.06. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 23.06. 16:45 - 18:15 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

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
- shortest paths
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
- joint discussions of exercises and according solutions
- practical implementation of algorithms

Art der Leistungskontrolle und erlaubte Hilfsmittel

Students collect points with the following actions:
- homework exercises: students prepare solutions to given exercises and upload them in Moodle (max. 20 points)
- programming exercise: students implement a selected algorithm (max. 30 points)
- online open book exam in Moodle (max. 50 points)

Mindestanforderungen und Beurteilungsmaßstab

- Attendance at the lecture / exercise units is NOT required, except for the FIRST lecture on March 3.
- The grade is determined by the total number of points collected:
1: 89 - 100
2: 76 - 88
3: 63 - 75
4: 50 - 62
5: 0 - 49
- There is NO minimal required number of points for each action.

Prüfungsstoff

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

Literatur

- 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

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 07.09.2020 15:20