1 citations · 2 across the 5 of their papers we have counts for
5 papers
Learning to Optimize: Joint Routing and Flow Allocation on Sparse Non-Euclidean Networks
Haomiao Sun, Fang He, Congyuan Ji +1
We study an integrated pickup-and-delivery problem on sparse, non-Euclidean networks that jointly optimizes cyclic routing, cargo flow allocation, and cross-cycle service. The tigh…
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…
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…
Online Relocating and Matching of Ride-Hailing Services: A Model-Based Modular Approach
Chang Gao, Xi Lin, Fang He +1
This study proposes an innovative model-based modular approach (MMA) to dynamically optimize order matching and vehicle relocation in a ride-hailing platform. MMA utilizes a two-la…
Vehicle Dispatching and Routing of On-Demand Intercity Ride-Pooling Services: A Multi-Agent Hierarchical Reinforcement Learning Approach
Jinhua Si, Fang He, Xi Lin +1
The integrated development of city clusters has given rise to an increasing demand for intercity travel. Intercity ride-pooling service exhibits considerable potential in upgrading…