goods movement

This project proposes to improve vehicle utilization and energy efficiency by modeling and evaluating the innovative shared mobility services for freight, with a specific focus on on-demand food delivery. Overall, the shared mobility service has great potential to reduce freight transportation VMT cost and emission. With well-designed delivery policy, the on-demand food delivery can mitigate traffic in the urban city and bring a greener transportation system.

In this research, the team studied a dynamic on-demand food delivery system and proposed a rolling horizon-based optimization approach integrated with adaptive large neighborhood search (ALNS) to efficiently obtain high-quality solutions. The system-level evaluation shows that on-demand food delivery has great potential to reduce dining-related VMT, resulting in significant reductions of fuel consumption and emissions, especially with Multi-R delivery policy.