Online 3D Bin Packing

Online 3D bin packing focuses on efficiently arranging a sequence of three-dimensional objects into a container, maximizing space utilization. Current research heavily utilizes deep reinforcement learning (DRL), often employing transformer networks or integrating physics-based heuristics to improve packing performance and generalization across different container sizes. These advancements aim to optimize logistics and automation processes, particularly in robotics and warehousing, by providing more efficient and robust solutions to this computationally complex problem. The development of more generalizable and robust algorithms is a key focus, addressing challenges like unpredictable item sequences and real-world physical constraints.