Integrated Container Slot Allocation and Automated Stacking Crane Scheduling in Automated Container Terminals with Limited Buffers

Abstract

This paper investigates the integrated scheduling of automated stacking cranes (ASCs) and container slot allocation in automated container terminals (ACTs) with limited buffer capacity. A hybrid stacking strategy based on time windows is proposed, and a bi-objective mixed-integer programming model is developed, considering automated guided vehicles and truck buffer capacities, ASC safety distances, and handshake area operations. An enhanced non-dominated sorting genetic algorithm II with tabu search (NSGA-II-TS) is designed, with parameters optimized via sensitivity analysis. Experiment results show that comparisons with an exact mixed-integer linear programming solver validate the solution quality of the proposed approach, and that the proposed algorithm significantly outperforms benchmark heuristic methods in generating high-quality Pareto-optimal solutions. Case studies reveal that dynamically adjusting handshake area locations and setting buffer capacity to six units effectively balance container flow and operational costs. The proposed approach is also validated against two alternative scheduling strategies, demonstrating superior effectiveness. This research provides new strategies and a robust method for improving the operational efficiency of ACTs under buffer constraints.