Teaching at the Institute of Production Management

• Optimization problems and methods
• Modeling practical optimization problems
• Implementation of mathematical programs
• Python/LaTeX

This seminar covers basic models and algorithms of operations management at the bachelor's level and provides practice in writing a paper in preparation for a bachelor's thesis at the Institute for Production Management.

Will be announced at the beginning of the semester.

Examiner: Prof. Dr. Helber

This course treats fundamental aspects of algebraic modeling and using optimization methods in operations research. Students are introduced to the improving search paradigm, in particular over convex feasible sets. The simplex search for linear programming models is covered, including a first treatment of duality of LP models. With respect to discrete problems, the basic elements of the branch&bound method are introduced. We further study column generation and elements of Branch-and-Price or Bender's decomposition.The GAMS modeling language is used in modeling exercises.

Rardin, R. L.: Optimization in Operations Research, 2. Edition 2016 (Pearson)

The supplementary (optional) exercise accompanies the lecture on Operations Research. Selected problems and tasks from the text book by Rardin (2016) are used to practice the lecture's methods and algorithms.

The course covers various operational decision-making problems in the design of industrial production processes in the field of material goods production. These include, in particular, issues relating to the planning of overtime and inventory levels, the planning of batch sizes and sequences, and production control. The conceptual foundations of various approaches to production planning and control are also covered.

A detailed script will be provided during the course.

The course requires a broad knowledge of basic quantitative methods, which are taught in the course “Operations Research.” It is therefore strongly recommended to take this course beforehand or at the same time.

The course covers selected topics from the field of economics that are required for working on the project within the framework of ‘Kooperatives Produkt’ (KPE).
The topics are selected according to the requirements of the current KPE project and the participants' knowledge background and wishes. Possible topics include:

• Production optimisation
• Logistics
• Investment calculation
• Process planning
• Marketing
• Cost and revenue accounting
• Cost management
• Product management

Towards the end of the course, individual group consultation hours on economic issues relating to the KPE can also be offered.
In addition, trial presentations for the interim and final presentations of the KPE will take place.

• Helber: Operations Management Tutorial (2020, 2. Auflage), Verlag: Stefan Helber
• Meffert, Burmann, Kirchgeorg: Marketing: Grundlagen marktorientierter Unternehmensführung; Konzepte - Instrumente - Praxisbeispiele (2012, 11. Auflage), Gabler Verlag.
• Friedl, Hofmann, Pedell: Kostenrechnung: eine entscheidungsorientierte Einführung (2010), Vahlen Verlag.
• Günther, Tempelmeier: Produktion und Logistik (2012, 12. Auflage), Springer Verlag.
• Domschke, Drexl: Einführung in Operations Research (2011, 8. Auflage), Springer Verlag.
• Kuhner, Maltry: Unternehmensbewertung (2017, 2. Auflage), Springer Verlag.

The number of participants is limited. The selection process will be carried out by the IPH (Institute for Integrated Production Hannover). The examination number is: 23710. The course is held in German only.

As part of the Operations Management colloquium, students who are writing their thesis in the area Operations Management present their progress during the course of their work. In addition, open questions regarding methodology and content can be discussed during the course of the work. Furthermore, the institute's researchers report on ongoing research projects, in particular doctoral projects, as part of this colloquium.

The seminar covers current scientific publications in the aforementioned field. As part of the course, students are typically required to implement algebraic decision models addressing problems in operations management using Python and Gurobi or GAMS, and to analyze them experimentally.

Will be given at the beginning of the semester.

There will be a combined lecture and exercise covering the following topics:

• Python and Visual Studio Code
• Git and UV
• Selection and structure of suitable data structures
• Object-oriented programming
• Implementation of algorithms
• Mathematical models in gurobipy
• Profiling and debugging methods
• Data analysis with pandas
• Visualisation with matplotlib

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Course registration: The number of participants is limited to 21. Applications for the course must be submitted via the Institute's website by Tuesday, 13 October. Particular consideration will be given to any courses you have already taken at the Institute of Production Management during your Bachelor's and Master's degrees, as well as your Bachelor's thesis. Any remaining places will be allocated during the first lecture.

Examination format: The examination consists of three assignments (programming tasks) during the semester, which are completed in groups, plus three oral examinations. The groups are randomly reassigned after each programming task.

Advanced project & credit: Building on this course, the advanced course “Implementation of OM Models and Methods in Python – Advanced Project” can be taken in the same semester, which includes another assignment. Students in the “Industrial Engineering” program can alternatively have the combination of these two courses credited as “Scientific Computing” (10 LP).

Building on the course “Implementation of OM Models and Methods in Python,” this course aims to deepen students' knowledge of programming with Python. To this end, students will work independently in groups to complete a task from the field of operations research and write an assignment on it.

Prerequisites: The course can only be taken in combination with the lecture “Implementation of OM Models and Methods in Python” in the same semester.

Credits as scientific computing: Students in the “Engineering and Business Administration” program can alternatively have the combination of “Implementation of OM Models and Methods in Python” and “Implementation of OM Models and Methods in Python - Advanced Project” credited as “Scientific Computing” (10 LP).

The subject of the course is the development of forecasting methods, in particular for the demand for goods and services over time, which form the basis for operational planning, such as the production program, or provide a basis for personnel planning. For this purpose, regression models are constructed using Python, which accurately reflect past observation data and can thus be interpreted as a model of the data-generating process. In these models, particular emphasis is placed on modeling the impact of influencing factors such as advertising measures, which are subject to operational decisions.

Lecture notes are availabe, as well as 20 copies of Francis X. Diebold's textbook, Elements of Forecasting, 4th edition, 2007, at the TIB library.

This course requires programming skills in Python and a high degree of independence in your work.

Exam date: Tuesday, February 2, 2027, from 9:30 to 10:30 a.m.