Jan-Niklas Dörr

Doctoral candidate

Email: jan.doerr(at)tum.de
Phone: +49 (0)89 289 24878
Room: 1531 (building 0505)

Research interests

Since 05/2022	Research associate Chair of Production and Supply Chain Management Technical University of Munich, Germany
10/2019 – 04/2022	M.Sc. Management and Technology Technical University of Munich, Germany
10/2015 – 06/2019	B.Sc. Management and Technology Technical University of Munich, Germany
10/2012 – 10/2019	Teaching degree in Mathematics and Physical Education Ludwig Maximilian University Munich, Germany

(Keine Dokumente in dieser Ansicht)

Doerr, J; Pahr, A.; Grunow, M.: Exploring the Benefits of Dynamic Scheduling in Complex Manufacturing Settings. (Vortrag / 8th Stochastic Modelling Meeting (Milano)) 2024 mehr…
Doerr, J; Pahr, A.; Grunow, M.: Exploring the Benefits of Dynamic Scheduling in Complex Manufacturing Settings. (Vortrag / GPOM Summer 2024) 2024 mehr…
Doerr, Jan-Niklas: Action space designs for stochastic production scheduling with sequence-dependent setup times. (Vortrag / QBWL (Bad Windsheim)) 2023 mehr…
Doerr, Jan-Niklas: Action space designs for dynamic scheduling with uncertain processing times and sequence-dependent setup times. (Vortrag) 2022 mehr…
Doerr, Jan-Niklas: Action space designs for dynamic scheduling with uncertain processing times and sequence-dependent setup times. (Vortrag / OR 2022 (Karlsruhe)) 2022 mehr…

Brendstrup, M.: Online Scheduling via Priority Functions with State-dependent Weights. Masterarbeit, 2024 mehr…
Cheng, C.: Online Lot Scheduling with Order Aggregation. Masterarbeit, 2024 mehr…
Boe Krogh, H.: Deep Reinforcement Learning in Production Scheduling. Masterarbeit, 2023 mehr…
Zlatanov, V. : Reinforcement Learning for Multi-Echelon Inventory Management. Masterarbeit, 2023 mehr…

Hellwig, L.: Enhancing Interpretability in Constraint Programming: Introducing a Lower Bound for a Flexible Flow Shop Scheduling Problem with Sequence-Dependent Setup Times. Bachelorarbeit, 2023 mehr…

Rao, R: Adaptive Scheduling for Production Systems using Deep Reinforcement Learning. IDP-Arbeit, 2025 mehr…
Gleisberg, A.; Salkic, E.: Batching and Lot Streaming via Deep Learning. IDP-Arbeit, 2025 mehr…
Augsburger, D.: Supply Chain Optimization through Preventative Risk Management and Hotspot Detection. IDP-Arbeit, 2025 mehr…
Zhou, L.: Building a remote server infrastructure to conduct scientific computing in operations research. IDP-Arbeit, 2024 mehr…
Çakr, H.: Using Graph Neural Networks to Solve Scheduling Problems. IDP-Arbeit, 2024 mehr…
Creteanu, C.: Creating a Real Time Visualization for the Reports in the R&S Report Manager. IDP-Arbeit, 2023 mehr…
Kormann, M.: Optimization of Order Delivery Scheduling. IDP-Arbeit, 2023 mehr…
Doganay, C. ; Mihaescu, T.: Replicated Data View Applications for the EPR Solution. IDP-Arbeit, 2023 mehr…