Rudy Negenborn Full Professor Main Publications Team & Themes Education Resume

Science in pictures To the point: Component sizing and energy management for SOFC-based ship power systems "The shipping industry is facing increasing demands to reduce its environmental footprints. This has resulted in adoption of new and more environmental friendly power sources and fuels for on-board power generation. One of these novel power sources is the Solid Oxide Fuel Cell (SOFC) which has a great potential to act as a power source, thanks to its high efficiency and capability to handle a wide ..." [More...] Component sizing and energy management for SOFC-based ship power systems. A. Haseltalab, L. van Biert, H.D. Shapra, B.T.W. Mestemaker, R.R. Negenborn. Energy Conversion and Management, vol. 245, no. 114625, October 2021. Open access.    Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning "The objective of this study is to address the issue of service time uncertainty in synchromodal freight transport, which can cause delays, inefficiencies, and reduced satisfaction for shippers. The proposed solution is an online deep Reinforcement Learning (RL) approach that takes into account the service time uncertainty, assisted by an Adaptive Large Neighborhood Search (ALNS) heuristic that pro..." [More...] Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning. Y. Zhang, R.R. Negenborn, B. Atasoy. Transportation Research Part C: Emerging Technologies, vol. 156, no. 104355, November 2023. Open access.    Multi-area predictive control for combined electricity and natural gas systems "The optimal operation of an integrated electricity and natural gas system is investigated. The couplings between these two systems are modeled by energy hubs, which serve as interface between the loads and the transmission infrastructures. Previously, we have applied a distributed control scheme to a static three-hub benchmark system. In this paper, we propose an extension of this distributed cont..." [More...] Multi-area predictive control for combined electricity and natural gas systems. M. Arnold, R.R. Negenborn, G. Andersson, B. De Schutter. In Proceedings of the European Control Conference 2009 (ECC'09), Budapest, Hungary, pp. 1408-1413, August 2009.    The value of information sharing for platform-based collaborative vehicle routing "Cooperation is important in order to find efficient vehicle routing solutions for the growing transportation market. Increasingly, platforms emerge as facilitators for this kind of collaborative transportation. However, individual actors connected to a platform might refuse to share (parts of) their information due to reasons of competition. Though the need for realistic information sharing models..." [More...] The value of information sharing for platform-based collaborative vehicle routing. J. Los, F. Schulte, M.T.J. Spaan, R.R. Negenborn. Transportation Research Part E: Logistics and Transportation Review, vol. 141, no. 102011, September 2020.    The value of information sharing for platform-based collaborative vehicle routing "Cooperation is important in order to find efficient vehicle routing solutions for the growing transportation market. Increasingly, platforms emerge as facilitators for this kind of collaborative transportation. However, individual actors connected to a platform might refuse to share (parts of) their information due to reasons of competition. Though the need for realistic information sharing models..." [More...] The value of information sharing for platform-based collaborative vehicle routing. J. Los, F. Schulte, M.T.J. Spaan, R.R. Negenborn. Transportation Research Part E: Logistics and Transportation Review, vol. 141, no. 102011, September 2020.    Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning "The objective of this study is to address the issue of service time uncertainty in synchromodal freight transport, which can cause delays, inefficiencies, and reduced satisfaction for shippers. The proposed solution is an online deep Reinforcement Learning (RL) approach that takes into account the service time uncertainty, assisted by an Adaptive Large Neighborhood Search (ALNS) heuristic that pro..." [More...] Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning. Y. Zhang, R.R. Negenborn, B. Atasoy. Transportation Research Part C: Emerging Technologies, vol. 156, no. 104355, November 2023. Open access.    Even more to the point: