3 accepted papers
Shared micromobility services such as e-scooters and bikes have become an integral part of urban transportation, yet their efficiency critically depends on effective vehicle rebalancing. Existing methods either optimize for average demand patterns or employ robust optimization and reinforcement lear…
Time series forecasting has long relied on dense endogenous observations, yet in many real-world scenarios, such data is scarce or even absent. Existing approaches attempt to compensate with exogenous variables, but their reliance on incomplete endogenous histories makes them brittle under data scar…
Shared electric micromobility has surged to a popular model of urban transportation due to its efficiency in short-distance trips and environmentally friendly characteristics compared to traditional automobiles. However, managing thousands of shared electric micromobility vehicles including rebalanc…