Problem-Based Learning Of Heuristic Methods For Decision Problems In Mathematics, Computer Science And Industrial Engineering

In a digitalized world, most processes can be formalised, measured and described mathematically. The use of analytical methods to optimise such models and decisions constitutes operational research (OR), developing new methods for a specific problem and analysing them are part of discrete optimisation (DO). However, there is limited research on OR and application driven DO in higher education. Furthermore, neither is well integrated into engineering education research. In this work, we present a case study of an interdisciplinary Master’s course on heuristic methods in the context of OR and DO. We discuss to what extent wellestablished approaches from engineering education practice, such as ProblemBased Learning, are applicable. Furthermore, we introduce two practical cases and argue that due to its application-oriented nature, OR and DO specifically stimulate independent student work. Results from evaluations, minute papers and student coursework indicate that the teaching approach successfully contributed to students’ achievement of the intended learning outcomes. To further foster discussion, we not only provide the lecture notes publicly, but also all tutorial and project case data to instructors upon request under a CC BY-NC license.