AdONE develops new mathematical models and computational methods for efficient resource allocation and coordination among multiple parties in dynamic logistics networks, transportation, and mobility systems. 

Our work is at the intersection of mathematics, computer science, and management science, driven by exciting applications such as airport operations, auction mechanisms for network procurement, autonomous mobility, carsharing systems, production planning, vehicle routing, warehousing & e-commerce. 

The PhD program is jointly hosted by the School of Management and the School of Computation, Information and Technology at TUM. We are funded by the German Science Foundation (DFG) as a "Research Training Group". 

As part of AdONE, we want to combine complex mathematical approaches from the Operations Research (OR) field with Business Process Management (BPM). At the intersection of BPM and OR we expect great potential for process performance improvement. Bringing both areas closer together, means tying optimization algorithms closer to the process execution and using process related data to improve optimization algorithms. Typical use cases are resource allocation and scheduling. Predictive process monitoring (PPM) and predictive compliance monitoring (PCM) can be applied to the OR domain as well, aiming to optimize the distribution of resources and mitigate potential risks in advance.

At our chair, Prof. Rinderle-Ma serves as a Principal Investigator (PI) for the AdONE project. Qian Chen and Felix Schumann are part of the AdONE interdisciplinary PHD Program.





  • Mangat, Amolkirat Singh; Rinderle-Ma, Stefanie: Next-Activity Prediction for Non-stationary Processes with Unseen Data Variability. Enterprise Design, Operations, and Computing, 2022 mehr… BibTeX Volltext ( DOI )
  • Rinderle-Ma, Stefanie; Winter, Karolin: Predictive Compliance Monitoring in Process-Aware Information Systems: State of the Art, Functionalities, Research Directions. arXiv, 2022, mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)