Research on Yard Segment Allocation of Automated Container Terminals Considering Vessel Arrival Uncertainty

Automated Container Terminals (ACTs) are increasingly challenged by uncertain vessel arrival times, which cause fluctuations in unloading demand and disrupt pre-established yard allocation plans. To address this issue, this study develops a yard allocation model integrating dynamic inventory, main-road capacity constraints, and collaborative yard crane operations. The model jointly minimizes the range of traffic flows across periods and the range of terminal inventory levels across yard segments, aiming to improve traffic smoothness and spatial balance. An Improved Detective Behavior Algorithm (IDBA) is proposed to solve the model efficiently. It adopts a discrete encoding scheme tailored to segment allocation and incorporates an adaptively decaying Lévy step size, coding-feature perturbation, and an annealing acceptance criterion. Numerical experiments show that IDBA outperforms benchmark algorithms in solution quality and stability. The results further reveal a trade-off between traffic smoothness and spatial equilibrium and demonstrate that uncertainty in vessel arrivals adversely affects established yard storage plans. This study provides quantitative support for refined yard scheduling in ACTs under complex constraints and uncertain operating environments.