OPM 662: Business Analytics: Modeling and Optimization
Contents
Business Analytics helps to optimize decisions for the design and management of operations systems and production processes. This course introduces concepts and tools for prescriptive analytics for modeling and optimization based on techniques from Operations Research. Operational and tactical planning tasks are formulated as linear and mixed integer linear programming models. All lectures will be given in a computer lab, where the optimization models are implemented and solved using standard tools of prescriptive analytics. Different heuristic techniques to cope with the complexity of real world scheduling problems are introduced and implemented. Data-driven approaches to cope with stochastic variability are introduced and analyzed. During the course the students will work on several case studies and assignments (individual and in groups).
Learning outcomes
Students learn how to structure operations planning and scheduling problems. They are able to translate them into mixed integer linear models. Students learn how to use Python to implement them and solve them with a standard solver to derive optimal plans/
Necessary prerequisites
Modules OPM 560 and OPM 561
Recommended prerequisites
The course assumes a basic knowledge in mathematics (including linear programming).
| Forms of teaching and learning | Contact hours | Independent study time |
|---|---|---|
| Lecture with intergrated exercise | 4 SWS | 13 SWS |
| ECTS credits | 6 |
| Graded | yes |
| Workload | 180h |
| Language | English |
| Form of assessment | Assignments and presentations (70%), written exam (45 min.) or oral exam (30%) |
| Restricted admission | yes |
| Further information | – |
Examiner Performing lecturer |  | Prof. Dr. Raik Stolletz Prof. Dr. Raik Stolletz |
| Frequency of offering | Spring semester |
| Duration of module | 1 semester |
| Range of application | M.Sc. MMM, M.Sc. Bus. Edu., M.Sc. Econ., M.Sc. Bus. Inf., M.Sc. Bus. Math. |
| Preliminary course work | – |
| Program-specific Competency Goals | CG 1, CG 4 |
| Literature | Will be announced during the lecture |
| Course outline | Please note that this outline will be subject to changes: Applications of optimization models
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