Universität Wien

040894 KU LP Modeling I (MA) (2021W)

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

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 35 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

The course format this semester will be hybrid. New content will be mostly discussed in live online classes. On Nov. 26th, there will be a the possibility to practice programming on-site at OMP.
Exams will take place on-site at OMP on Nov. 18th, and Dec. 16th, closed book.
The mode might be adaped if Corona rules change.

  • Donnerstag 07.10. 09:45 - 13:00 Digital
  • Donnerstag 14.10. 09:45 - 13:00 Digital
  • Donnerstag 21.10. 09:45 - 13:00 Digital
  • Donnerstag 28.10. 09:45 - 13:00 Digital
  • Donnerstag 04.11. 09:45 - 13:00 Digital
  • Donnerstag 11.11. 09:45 - 13:00 Digital
  • Donnerstag 18.11. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
    PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
    PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 19.11. 09:45 - 13:00 Digital
  • Donnerstag 25.11. 09:45 - 13:00 Digital
  • Freitag 26.11. 09:45 - 13:00 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
    PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Donnerstag 02.12. 09:45 - 11:10 Digital
  • Donnerstag 16.12. 09:45 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Donnerstag 13.01. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The course introduces students to modeling techniques in the area of linear programming. To gain a better understanding about the underlying problems and solution techniques the following topics will be discussed:

Introduction to Linear Programming
Introduction to Mosel / XPress-MP
Simplex Method (brief repetition)
Sensitivity Analysis & its economic interpretation
Introduction to (mixed) integer programming
Modeling with binary variables

New content will be provided as slides with audio comments. Homework examples have to be solved individually and have to be uploaded in Moodle. There will be an online tutorial (Nov. 19th) for implementing simple LP models in Mosel. On Nov 26th students can practice their implementation skills under supervision in the PC lab (attendance not mandatory).

Art der Leistungskontrolle und erlaubte Hilfsmittel

20 % homework
40 % midterm exam (on-site) (Nov, 18th, 2021)
40 % final exam (onsite) (Dec, 16th, 2021)

Mindestanforderungen und Beurteilungsmaßstab

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

The other grades are distributed as follows:
4: 50% to <63%
3: 63% to <75%
2: 75% to <87%
1: 87% to 100%

Prüfungsstoff

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

Content of the exams:
- Formulation of LP models
- Graphical solution method
- The Simplex algorithm
- Duality
- Sensitivity analysis
- Mosel / XPress
- Branch-and-bound
- Modeling with binary variables
- Formulation of specific objectives

The final exam will additionally include parts where students need to show the implementation skills acquired during lessons and homework (e.g. how the implementation of a certain constraint would look like, how one has to declare variables, etc.) and by explaining a given Mosel code and/or finding errors in it.

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: Fr 12.05.2023 00:13