Universität Wien FIND
Achtung: Derzeit finden keine Lehrveranstaltungen und Prüfungen an der Universität Wien statt, der Lehrbetrieb wird auf home-learning und e-Learning umgestellt. Bei ordnungsgemäßer Anmeldung zu einer Prüfung / Lehrveranstaltung gelten die in u:find bzw. Moodle kommunizierten geänderten Prüfungsmodi als akzeptiert. Weitere Informationen finden Sie hier.

040127 KU Transportation Logistics (MA) (2018W)

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

The course language is English.

Only students who signed up for the class in univis/u:space are allowed to take the class (that means, that you have to at least be on the waiting list if you want to take this class). No exceptions possible.

Details

max. 60 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Montag 01.10. 13:15 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Montag 08.10. 13:15 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Montag 15.10. 13:15 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag 23.10. 11:30 - 14:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Montag 29.10. 13:15 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Montag 05.11. 13:15 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Montag 12.11. 13:15 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Montag 19.11. 13:15 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Montag 26.11. 13:15 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course is an introduction to some optimisation problems that appear in Transportation Logistics. Along the semester, we will cover several of these problems, and study their corresponding mathematical formulations and solution methods.
Among the problems we will study: classical network problems (minimum spanning tree, shortest paths, maximum flows), warehouse location problem and its capacitated version, transportation problem, assignment problem, knapsack problem, orienteering, traveling salesman and vehicle routing problems, and maybe others.
Among the methods we will learn: combinatorial algorithms, modelling and solving network problems as linear programs, simplex, dynamic programming, and (for the harder problems), branch-and-bound. For some of the hard problems, we will also discuss construction and improvement heuristics.
This course is broad rather than deep, which means that we emphasise covering a good number of problems and methods, without spending too much time in any of them. The focus is on learning methods, and developing intuition behind why they work.

Art der Leistungskontrolle und erlaubte Hilfsmittel

2 exams, each corresponding to 40% of the final grade.
Several homeworks to be announced every week, and handed in in the beginning of the following class. These account for the remaining 20% of the grade.

Mindestanforderungen und Beurteilungsmaßstab

Students should be familiar with Excel (in special, the Solver), and have basic knowledge about linear programming (i.e., understand a LP formulation, and how to apply the simplex method).
This course requires a somewhat higher level of abstraction, when compared to a Bachelor course. Students are expected to spend around 1-2 hours per week in out-of-class studies (reviewing the content, and preparing the homeworks).

Prüfungsstoff

Literatur

Slides will be available through Moodle, and are sufficient for covering all the content of the course.
For a quick review of linear programming, including the simplex method, students are referred to:
Hillier, Lieberman. Introduction to Operations Research. Chapters 1-5.
(Optional!) For a deeper and more rigorous understanding of many of the methods we see in this course, students are referred to:
Bertsimas, D., Tsitsiklis, J. Introduction to Linear Optimization.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mi 13.03.2019 10:47