Achtung! Das Lehrangebot ist noch nicht vollständig und wird bis Semesterbeginn laufend ergänzt.
040247 KU Transportation Analytics and Optimization Tools (MA) (2024W)
Prüfungsimmanente Lehrveranstaltung
Labels
VOR-ORT
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 09.09.2024 09:00 bis Do 19.09.2024 12:00
- Anmeldung von Mi 25.09.2024 09:00 bis Do 26.09.2024 12:00
- Abmeldung bis Mo 14.10.2024 23:59
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- N Freitag 11.10. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Donnerstag 17.10. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Freitag 18.10. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Donnerstag 24.10. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Freitag 25.10. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Donnerstag 31.10. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Freitag 08.11. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Donnerstag 14.11. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Freitag 15.11. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Freitag 22.11. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Donnerstag 28.11. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Freitag 29.11. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Freitag 06.12. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Donnerstag 12.12. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Donnerstag 09.01. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Freitag 10.01. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Freitag 17.01. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Donnerstag 23.01. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Freitag 24.01. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
- Freitag 31.01. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
[25%] Midterm written exam (Friday 22nd of November)
[25%] Final written exam (Friday 31st of January)
[25%] Group project with presentation in class: Present a variant of the vehicle routing problem and explain a solution method from the literature. Discuss applications and shortcomings. (Submission of presentation until Thursday 12th of December, 23:59 and presentations on Friday, 13th of December 9:45 - 16:30h with breaks).
[25%] Homework assignments (modelling and coding in C++)The use of AI tools (e.g. ChatGPT) for the production of texts is not permitted!
[25%] Final written exam (Friday 31st of January)
[25%] Group project with presentation in class: Present a variant of the vehicle routing problem and explain a solution method from the literature. Discuss applications and shortcomings. (Submission of presentation until Thursday 12th of December, 23:59 and presentations on Friday, 13th of December 9:45 - 16:30h with breaks).
[25%] Homework assignments (modelling and coding in C++)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: Mi 04.09.2024 09:05
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.
A basic OR knowledge is strongly recommended. According to the flipped classroom principle, students will prepare a presentation in groups and present in class.
In the optimization tools part of the course, we will learn how solution methods can be implemented in C++. This includes several homework assignments. Experience in using modelling languages or coding is strongly recommended.Note: You can participate either in the course 'Transportation Analytics'
or in the course 'Transportation Analytics and Optimization Tools' (not in both)!