Analytics and Optimization Project

 

Content

In the Analytics and Optimization Project (AOP), students work in interdisciplinary groups (economics, industrial engineering, mathematics, computer science). Each group solves an application-oriented problem using methods from the fields of data analytics and operations research. Past topics have been provided by companies such as Deutsche Post DHL Group, Barkawi, Lufthansa, Ab Ovo and Picnic. Each group is supervised by a contact person from the company and a contact person from the chair during literature research, implementation of the chosen method and when preparing the presentations.

Prerequisites

Knowledge in the field of linear and integer programming; knowledge of a programming language (e.g. C++, Julia, Java, Python) or modeling language (e.g. GAMS, AIMMS) required; prior knowledge of heuristic optimization and data analytics is an advantage.

Organization

The AOP is a project module. Students must be present during four plenary sessions, which usually take place in the first, third, ninth and last lecture week of the summer semester. Students will find all the details via the project module registration process. Each topic is assigned to 3–6 students according to their preferences.

Organizational information on project modules is provided by the School of Business and Economics.

 

Learning Goals

  1. interdisciplinary communication
  2. collecting, cleaning, analyzing, interpreting and visualizing real data
  3. solving practical optimization problems using modeling languages and solvers but also by implementing problem-specific algorithms
  4. presenting and documenting project results professionally.
 

External Links