Universität Wien

040245 KU Transportation Analytics (MA) (2023S)

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

  • Thursday 02.03. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 09.03. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 16.03. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 23.03. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 30.03. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 20.04. 13:15 - 14:45 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 27.04. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 04.05. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 11.05. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Friday 12.05. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 25.05. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 01.06. 13:15 - 14:45 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 15.06. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 22.06. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Thursday 29.06. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Friday 30.06. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01

Information

Aims, contents and method of the course

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, metaheuristics, and large neighborhood search are covered. We will learn that for both, heuristic and exact methods, the solution of variants of the shortest path problem with resource constraints via dynamic program is a key component.
A basic OR knowledge is strongly recommended. According to the flipped classroom principle, students will prepare a presentation in groups and present in class.

Assessment and permitted materials

[30%] Midterm written exam
[30%] Final written exam
[40%] Group project with presentation in class. Students can choose between two types of project tasks:
a) Implementation: Solve a vehicle routing problem with a method learned in the lecture (via Excel Solver, modelling language and MIP-solver, or coding) and conduct a computational study.
b) Literature Work: Present a new variant of the vehicle routing problem, discuss applications and shortcomings, and explain how solution methods covered in the lecture must be adapted to deal with the problem.

Minimum requirements and assessment criteria

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

Examination topics

Lecture and exercise notes, literature excerpts

Reading list

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

Association in the course directory

Last modified: Tu 14.03.2023 11:28