Universität Wien FIND

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040897 KU LP Modeling II (MA) (2018S)

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

An/Abmeldung

Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Donnerstag 03.05. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag 17.05. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag 24.05. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag 07.06. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag 14.06. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag 21.06. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag 28.06. 09:45 - 11:15 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The course builds upon the knowledge gained in the course LP-Modeling I and introduces students to advanced modeling techniques. In particular, complex linear programming models in the fields of production, logistics and supply chain management are discussed. Besides the modeling aspects, an emphasis is given on the implementation of the models in XpressMP, which is then used to solve these models.

In addition to the classes, students are supposed to prepare different homework assignments, which they must be able to explain / present individually. The classes will consist of a short discussion of the homework assignments, a lecture part, and programming on the computers in the lab by the students.

Furthermore, there will be a group homework assignement where students need to understand, possibly adapt and implement an LP model from literature. There will be short presentations of the models at the end of the course.

At the end of the course students should be able to develop mathematical (linear programming) models for different problems that arise in production and logistics. Moreover, they will have acquired programming skills in Mosel (the programming language of XPress) in order to implement and solve these models by the use of XPressMP.

Art der Leistungskontrolle und erlaubte Hilfsmittel

25 % individual homework assignements
35 % group homework
5 % presentation
35 % final exam (closed book)

Mindestanforderungen und Beurteilungsmaßstab

In order to pass the course (minimum requirement) students have to achieve at least 50% in total.

Prüfungsstoff

Students are expected to understand, formulate and solve a variety of LP models and implement them using XpressMP. Slides will be available in Moodle.

Literatur

* Bertsimas, D., & Tsitsiklis, J. N. (1997). Introduction to linear optimization. Athena Scientific.
* Papadimitriou, C. H., & Steiglitz, K. (1998). Combinatorial Optimization: Algorithms and Complexity. Dover Publications.
* Guéret, C., Prins, C., & Sevaux, M. (2002). Applications of optimisation with Xpress-MP. Dash optimization.
* Hillier, F. S., & Lieberman, G. J. Introduction to Operations Research. McGraw-Hill.
* Anderson, D. R., Sweeney, D. J. An introduction to management science: quantitative approaches to decision making. South-Western.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 07.09.2020 15:29