Universität Wien
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040247 KU Transportation Analytics and Optimization Tools (MA) (2023W)

6.00 ECTS (3.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung
VOR-ORT
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

Mandatory presence for the presentation of the group projects: Friday, 15th of December (9:45 - 16:30 with breaks)

  • Freitag 06.10. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Freitag 13.10. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Donnerstag 19.10. 15:00 - 16:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 20.10. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Freitag 27.10. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Freitag 03.11. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Donnerstag 09.11. 15:00 - 16:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 10.11. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Freitag 17.11. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Donnerstag 23.11. 15:00 - 16:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 24.11. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Donnerstag 30.11. 15:00 - 16:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 01.12. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Donnerstag 07.12. 15:00 - 16:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 15.12. 09:45 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Freitag 15.12. 13:15 - 16:30 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Donnerstag 11.01. 15:00 - 16:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 12.01. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Donnerstag 18.01. 15:00 - 16:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 19.01. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Freitag 26.01. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course deals with basic and advanced methods for the resolution of vehicle routing problems. The course deals with classical and new variants of the vehicle routing problem, e.g., the vehicle routing problem with time windows, pick-up-and-delivery problems, and problems with synchronization aspects. Moreover, current trends in transport logistics are discussed (e.g., ride sharing, electric vehicles, sustainability aspects, ...).
The course focus on state-of-the-art components of exact as well as heuristic solution methods. Regarding exact methods, we learn about the components of branch-price-and-cut algorithms. On the heuristic side, local search methods and large neighborhood search are covered.
In the optimization tools part of the course, we will learn how solution methods can be implemented by using different optimization tools. These tools will be applied in several homework assignments.
A basic OR knowledge is strongly recommended. Experience in using modelling languages or coding is beneficial. According to the flipped classroom principle, students will prepare a presentation in groups and present in class.

Note: You can participate either in the course 'Transportation Analytics'
or in the course 'Transportation Analytics and Optimization Tools' (not in both)!

Art der Leistungskontrolle und erlaubte Hilfsmittel

[40%] Final written exam (Friday 26.01.2024 11:30 - 13:00)
[20%] Group project: Present a variant of the vehicle routing problem and explain a solution method from the literature. Discuss applications and shortcomings. (Submit until 4th of December 23:59)
[20%] Presentation of Group Project in class (Friday, 15th of December, 9:45 - 16:30 with breaks)
[20%] Homework assignments (modelling and coding)

The use of AI tools (e.g. ChatGPT) for the production of texts is not permitted!

Mindestanforderungen und Beurteilungsmaßstab

At least 50% of the overall total achievable score must be obtained for a positive grade.

Prüfungsstoff

Lecture and exercise notes, literature excerpts, usage of optimization tools

Literatur

Toth, P. and Vigo, D.: Vehicle Routing: Problems, Methods, and Applications. Philadelphia: SIAM, 2014. –ISBN 978-1-611973-58-7

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Do 19.10.2023 17:27