040894 KU LP Modeling I (MA) (2020W)
- Registration is open from Mo 14.09.2020 09:00 to We 23.09.2020 12:00
- Deregistration possible until Tu 27.10.2020 12:00
Classes (iCal) - next class is marked with N
Most of the content of the class will be provided on a weekly basis online in form of slides with audio comments. Correspondingly, there will be homework examples every week which have to be solved individually and have to be uploaded in Moodle.Live online sessions will be held on Oct. 1st, where the course modalities will be discussed, Nov. 5th (Mosel tutorial) and Oct. 22nd and Dec. 3rd (Q&A sessions for the exams).Instead of the classes planned for November in the PC Lab, which have to be cancelled due to the Corona situation, we will have a live session on Nov. 11th, 16:45.The midterm exam will be held on Oct. 29th, the final exam on Dec. 10th, both online.Additional details and updates will be provided in Moodle.
Aims, contents and method of the course
Assessment and permitted materials
40 % midterm exam (online) (Oct, 29th, 2020)
40 % final exam (online) (Dec, 10th, 2020)
Minimum requirements and assessment criteria
4: 50% to <63%
3: 63% to <75%
2: 75% to <87%
1: 87% to 100%
- Formulation of LP models
- Graphical solution method
- The Simplex algorithm
- Sensitivity analysis
- Mosel / XPress
- 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.
* 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.