Collaborative scheduling of external container trucks and yard cranes for resilient port operations

External container trucks and yard cranes are key equipment for yard operations in automated container terminals, and their operational efficiency is crucial to improving terminal service levels. In the context of growing uncertainties in global shipping—such as geopolitical conflicts, pandemics, and natural disasters—enhancing the resilience of port operations has become increasingly important. The uncertain arrival sequence of external container trucks within their appointment windows, coupled with the misalignment between container storage locations and truck arrival order, often leads to frequent container relocations in the yard. To address this issue, this paper develops a collaborative scheduling optimization model for external container trucks and yard cranes under a scenario of partial information availability, with the goal of minimizing the total cost of import container operations. In this context, operational resilience is realized through the model’s ability to swiftly recover efficiency by minimizing costs (e.g., reducing relocations and waiting times) via coordinated scheduling when facing the mismatch disruption. The model is solved using an improved Particle Swarm Optimization (PSO) algorithm, and the optimization outcomes are analyzed. Results demonstrate that by adjusting the number of trucks per group, optimizing the container retrieval sequence, and rationally assigning yard crane tasks, it is possible to reduce container relocation costs, truck waiting costs, and crane movement costs, thereby lowering the overall cost of import container operations and contributing to more resilient and intelligent yard management.