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040894 KU LP Modeling I (MA) (2022W)
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 12.09.2022 09:00 bis Fr 23.09.2022 12:00
- Anmeldung von Mi 28.09.2022 09:00 bis Do 29.09.2022 12:00
- Abmeldung bis Fr 14.10.2022 23:59
Details
max. 35 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
The course this semester will take place on-site at OPM. Most of the class content will be provided on a weekly basis. Correspondingly, there will be homework examples every week that have to be solved individually.
Exams will take place on-site at OMP on November, 17th and December 15th, closed book.
- Donnerstag 13.10. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Donnerstag 20.10. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Donnerstag 03.11. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Donnerstag 10.11. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Donnerstag 17.11. 11:30 - 13:00 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
- Donnerstag 24.11. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Donnerstag 01.12. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Donnerstag 15.12. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
20 % homework
40 % midterm exam (closed book, on-site) (date November, 17th, 2022)
40 % final exam (closed book, on-site) (date December, 15th, 2022)
40 % midterm exam (closed book, on-site) (date November, 17th, 2022)
40 % final exam (closed book, on-site) (date December, 15th, 2022)
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%
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 objectivesThe 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.
- 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 objectivesThe 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.
* 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 28.11.2022 10:08
Introduction to Mosel / XPress-MP
Simplex Method (brief repetition)
Sensitivity Analysis & its economic interpretation
Introduction to (mixed) integer programming
Modeling with binary variablesNew content will be provided weekly in class. Homework examples have to be solved individually. There will be a tutorial (Nov. 3rd) for implementing simple LP models in Mosel. On November 24th, students can practice their implementation skills under supervision in the PC lab (attendance not mandatory).