Endogenous FIFO-Batch Control for Dynamic Yard-to-Ferry Loading: A State-Aware Hierarchical Optimization Approach

Dynamic roll-on/roll-off terminals require an executable decision between yard planning and vessel stowage: which yard lane to release, how many accessible vehicles to move, and which ferry lane to receive the ordered batch. We formulate this interface as state-aware hierarchical batch control. Each action selects one yard queue, a FIFO-prefix length, and one receiving lane/deck, while complete enumeration screens compatibility, residual capacities, discharge order, slot continuity, and a transverse-moment envelope. All controllers receive the same physical execution-time budget, with one setup-time unit plus one unit per moved vehicle. A two-step beam model-predictive controller (HBC-MPC) minimizes the first-stage cost plus the optimal feasible second-stage cost and terminal backlog. We prove FIFO integrity, modeled action safety, recursive admissibility, completeness, and dominance of the endogenous feasible set over any included fixed size. The study uses 180 paired synthetic paths across three fleet regimes, three arrival intensities, and 20 seeds, yielding 1080 policy runs. Every final and intermediate feasibility audit passes. HBC-MPC loads 63.33 vehicles per sailing on average, versus 62.87 for myopic endogenous and largest-feasible control, 62.74 for fixed-four with cleanup, 44.53 for strict fixed-four, and 41.80 for strict fixed-six. Its mean weighted waiting area is 204.47, and its gain over strong adaptive baselines is modest but positive. The evidence supports state-dependent batching; predictive lookahead provides an additional benefit at substantially higher computation.