040894 KU LP Modeling I (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).

Registration is open from Mo 13.02.2023 09:00 to We 22.02.2023 12:00
Registration is open from Mo 27.02.2023 09:00 to Tu 28.02.2023 12:00
Deregistration possible until Fr 17.03.2023 23:59

Details

max. 35 participants

Language: English

Lecturers

Johanna Mlekusch

Classes (iCal) - next class is marked with N

The course this semester will take place on-site at OPM. The class content will be provided on a weekly basis. Correspondingly, there will be homework examples every week that have to be solved individually.

    
    Thursday
    02.03.
    09:45 - 13:00
    PC-Seminarraum 5  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Thursday
    09.03.
    09:45 - 13:00
    PC-Seminarraum 5  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Thursday
    16.03.
    09:45 - 13:00
    PC-Seminarraum 5  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Wednesday
    22.03.
    09:45 - 13:00
    PC-Seminarraum 1  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Thursday
    23.03.
    09:45 - 13:00
    PC-Seminarraum 5  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Wednesday
    29.03.
    13:15 - 14:45
    Hörsaal 1  Oskar-Morgenstern-Platz 1  Erdgeschoß
    
    Thursday
    20.04.
    09:45 - 13:00
    PC-Seminarraum 5  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Thursday
    27.04.
    09:45 - 13:00
    Hörsaal 4  Oskar-Morgenstern-Platz 1  Erdgeschoß

Information

Aims, contents and method of the course

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

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 weekly in class. Homework examples have to be solved individually and have to be uploaded to Moodle and presented in class. There will be a tutorial (Mar. 16th) for implementing simple LP models in Mosel. On March 22nd, students can practice their implementation skills under supervision in the PC lab (attendance not mandatory).

Assessment and permitted materials

20 % homework
40 % midterm exam (closed book, on-site) (date March, 29th, 2023)
40 % final exam (closed book, on-site) (date April, 27th, 2023)

Students have to upload the solutions of their homework in Moodle and present them in class.

Minimum requirements and assessment criteria

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%

Examination topics

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
- Solution methods
- 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 by writing Mosel code on paper (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.

Reading list

* 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.

Association in the course directory

Last modified: Tu 14.03.2023 11:28