A batch‐based method for the optimization of automated airport baggage loading

Abstract The rapid growth of civil aviation increases operational pressure on airport baggage handling systems. While robotic arms offer an automated alternative to manual processes, optimizing item placement for both loading efficiency and space utilization remains a critical challenge. This study formulates an online three‐dimensional loading problem to maximize trailer space utilization under operational constraints, including weight‐distribution constraints and pressure limits. We develop a batch‐based optimization algorithm with a physical buffer zone to dynamically group incoming baggage. The method integrates single‐bin serial and dual‐bin parallel loading modes with fixed and adaptive grouping strategies, supported by a staged multi‐objective evaluation function for sequence adjustment. Computational experiments show that the dual‐bin parallel mode with adaptive grouping achieves the best performance, improving average space utilization to 70.64% and outperforming the first‐in‐first‐out and OnlineBPH baselines. The proposed approach provides an effective and practical solution for automated loading operations in logistics and warehousing systems.