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cs.LG2026
A Retrieval-Enhanced Transformer for Multi-Step Port-of-Call Sequence Prediction in Global Liner Shipping
Yanzhao Su, Fang He, Yineng Wang
Accurate multi-step port-of-call sequence prediction is vital for tactical resource orchestration and logistical efficiency. However, existing methods struggle with unreliable voya…
cs.LG2026
Few-Shot Learning for Dynamic Operations of Automated Electric Taxi Fleets under Evolving Charging Infrastructure: A Meta-Deep Reinforcement Learning Approach
Xiaozhuang Li, Xindi Tang, Fang He
With the rapid expansion of electric vehicles (EVs) and charging infrastructure, the effective management of Autonomous Electric Taxi (AET) fleets faces a critical challenge in env…
cs.LG2026
Beyond the Next Port: A Multi-Task Transformer for Forecasting Future Voyage Segment Durations
Nairui Liu, Fang He, Xindi Tang +1
Accurate forecasts of segment-level sailing durations are fundamental to enhancing maritime schedule reliability and optimizing long-term port operations. However, conventional est…