| Dynamic priority based dispatching of AGVs in flexible job shops J Heger, T Voß Procedia Cirp 79, 445-449, 2019 | 32 | 2019 |
| Dynamically adjusting the k-values of the ATCS rule in a flexible flow shop scenario with reinforcement learning J Heger, T Voss International Journal of Production Research, 2021 | 25 | 2021 |
| Optimal scheduling of AGVs in a reentrant blocking job-shop J Heger, T Voss Procedia Cirp 67, 41-45, 2018 | 22 | 2018 |
| Reducing mean tardiness in a flexible job shop containing AGVs with optimized combinations of sequencing and routing rules J Heger, T Voss Procedia CIRP 81, 1136-1141, 2019 | 20 | 2019 |
| Dynamically Changing Sequencing Rules with Reinforcement Learning in a Job Shop System with Stochastic Influences J Heger, T Voss Proceedings of the 2020 Winter Simulation Conference, 1608 - 1618, 2020 | 14 | 2020 |
| A model predictive control in robotino and its implementation using ROS system P Mercorelli, T Voss, D Strassberger, O Sergiyenko, L Lindner 2016 International Conference on Electrical Systems for Aircraft, Railway …, 2016 | 8 | 2016 |
| Optimal trajectory generation using MPC in robotino and its implementation with ROS system P Mercorelli, T Voss, D Strassberger, O Sergiyenko, L Lindner 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE …, 2017 | 6 | 2017 |
| Optimal scheduling for automated guided vehicles (AGV) in blocking job-shops J Heger, T Voss Advances in Production Management Systems. The Path to Intelligent …, 2017 | 6 | 2017 |
| Simulation Based Optimization of Lot Sizes for Opposing Logistic Objectives JT Maier, T Voß, J Heger, M Schmidt IFIP International Conference on Advances in Production Management Systems …, 2019 | 4 | 2019 |
| Outperformed by a Computer?-Comparing Human Decisions to Reinforcement Learning Agents, Assigning Lot Sizes in a Learning Factory T Voß, A Rokoss, JT Maier, M Schmidt, J Heger Proceedings of the Conference on Learning Factories (CLF), 2021 | 3 | 2021 |
| Smarte Anpassung von Presslinienparametern-Bildgebende Sensorik und maschinelles Lernen für robustere Blechumformprozesse im Automobilbau J Heger, T Voβ, M Selent Industrie Management 4.0 34 (2018), 53-56, 2018 | 3 | 2018 |
| Dynamische Losgrößenoptimierung mit bestärkendem Lernen T Voß, C Bode, J Heger Zeitschrift für wirtschaftlichen Fabrikbetrieb 116 (11), 815-819, 2021 | 1 | 2021 |
| Entscheidungsbäume und bestärkendes Lernen zur dynamischen Auswahl von Reihenfolgeregeln in einem flexiblen Produktionssystem J Heger, MZ El Abdine, S Sekar, T Voß Simulation in Produktion und Logistik 2021: Erlangen, 15.-17. September 2021 …, 2021 | 1 | 2021 |
| Simulationsbasierte Optimierung zur Energieersparnis und Verbrauchsflexibilisierung in der Hinterlandentwässerung J Heger, T Voß Simulation in der Produktion und Logistik, 2019 | 1 | 2019 |
| Optimal robot scheduling of an AGV in the RCLL and introduction of team Leuphana T Voß, J Heger, N Meier, A Georgiadis Robocup, 2016 | 1 | 2016 |
| Methode zur dynamischen Anpassung von Reihenfolgeregeln mit bestärkendem Lernen T Voß Dissertation, Lüneburg, Leuphana Universität Lüneburg, 2022, 2023 | | 2023 |
| Dynamic Lot Size Optimization with Reinforcement Learning T Voss, C Bode, J Heger International Conference on Dynamics in Logistics, 376-385, 2022 | | 2022 |
| Simulation von kombinierter Stau- und Routenplanung in Multi-Terminal Häfen J Franzkeit, T Voß, H Pache, J Heger, C Jahn Simulation in Produktion und Logistik 2021: Erlangen, 15.-17. September 2021 …, 2021 | | 2021 |
| Simulationsbasierte Bewertung von intralogistischen Prozessen am Beispiel der Warenbereitstellung im Einzelhandel S Wenzel, T Peter Simulation in Produktion und Logistik 2017, 287, 2017 | | 2017 |
Jens HegerProfessor for Modelling and Simulation of Technical Systems and ProcessesПодтвержден адрес электронной почты в домене leuphana.de
