JuModel – Developing Models and Algorithms in the Cloud
- Current Projects
- Simulation and Logistics Engineering
Background
Simulation and optimization are essential components of science and engineering degree programs. However, current teaching formats often fail to utilize the potential of modern applications and interdisciplinary collaboration fully.
The courses " Methoden zur Planung und Steuerung der Transportlogistik " and "Modellgestützte Analyse und Optimierung " share the common goal of enabling students to develop skills in simulation and optimization, particularly in logistical systems So far, much time has been spent on familiarizing students with the software. Therefore, the aim is to achieve low-threshold didactic and methodological integration. The cloud-based platform JupyterHub.nrw is used for interdisciplinary collaboration on real application cases.
To implement this project, the Institute of Transport Logistics (ITL) from the Faculty of Mechanical Engineering, the Chair of Modeling and Simulation (Informatics 4) from the Faculty of Computer Science, and the Center for Higher Education (zhb) at TU Dortmund are cooperating.
Approach
An iterative approach ensures the continuous integration of project results into courses. In addition to the early use of project results in teaching, this approach enables several evaluation loops and the involvement of students.
The project takes a holistic approach to improving students' technical and methodological education. A central component is the curricular integration of software development aspects into courses focusing on logistics.
Another key element is case studies, where students independently tackle transport logistics problems using digital tools. Programming and simulation tools such as JupyterHub and AnyLogic are crucial. This project-based learning approach fosters explicitly students' ability to solve problems independently.
Project Goals
The project JuModel aims to integrate aspects of software development into a logistics course and to increase the practical relevance of a computer science course. Through an interdisciplinary case study with a transport logistics problem, students of logistics and computer science work together. This addresses the frequent criticism of a lack of practical relevance in higher education, higher taxonomy levels, and constructive alignment. The interdisciplinary collaboration enables students to acquire future skills such as agile working, digital collaboration, creativity, and data analytics.
Funding and Partners:
