"Motion control is one of the most critical aspects in the design of autonomousships. During maneuvering, the dynamics of propellers as well as the craft hy-drodynamical specifications experience sever uncertainties. In this paper, anadaptive control approach is proposed to control the motion and trajectorytracking of an autonomous vessel by adopting neural networks that is used f..." [More...]
"In North-West Europe, the options for intermodal inland transportation of containers are increasing. Inland corridors become increasingly interconnected in hinterland networks. To minimize operating costs, new methods are required that allow integral network operations management. The network operations consist of allocating containers to available inland transportation services, i.e. planning. Fo..." [More...]
"We propose closed-loop energy-efficient scheduling and control of an autonomous Inter Terminal Transport (ITT) system using waterborne Autonomous Guided Vessels (waterborne AGVs). A novel pick-up and delivery problem considering safe intervals between berthing time slots of different waterborne AGVs is proposed. Waterborne AGVs are controlled in a cooperative distributed way to carry out assigned ..." [More...]
"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...]
"Motion control is one of the most critical aspects in the design of autonomousships. During maneuvering, the dynamics of propellers as well as the craft hy-drodynamical specifications experience sever uncertainties. In this paper, anadaptive control approach is proposed to control the motion and trajectorytracking of an autonomous vessel by adopting neural networks that is used f..." [More...]
"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...]
