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1299. On-Time Meal Delivery Assisted by Drone Resupply
Invited abstract in session MB-64: Routing Unmanned Aerial Vehicles 1, stream VeRoLog - Vehicle Routing and Logistics.
Monday, 10:30-12:00Room: S16 (building: 101)
Authors (first author is the speaker)
| 1. | Wenqian Liu
|
| Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology | |
| 2. | Lindong Liu
|
| Management Science, University of Science and Technology of China | |
| 3. | XIANGTONG QI
|
| HKUST |
Abstract
With the competition between online meal delivery services growing, on-time delivery has become a crucial target for meal delivery platforms to pursue, thus calling for new technologies and operational models. Echoing such a need, we propose a drone resupply approach for meal delivery, where drones transport meals from restaurants to riders en route, and then riders deliver these meals to customers. This model involves the coordination of multiple trucks, drones, and depots, as well as the joint optimization of rider routing and drone scheduling. Our two-phase algorithm solves the problem by first identifying feasible rider routes along with the respective drone schedule for serving order bundles, and second, selecting rider routes using a set covering model. To address the issue of long service periods, we propose a rolling horizon strategy to solve it dynamically. Extensive computational studies are conducted to evaluate the efficiency of the solution method and the effectiveness of the drone-assisted delivery system. The results demonstrate that adopting drone resupply in meal delivery is more efficient than the traditional rider-only mode for maintaining the target on-time service level in large service areas.
Keywords
- Logistics
- Vehicle Routing
- Combinatorial Optimization
Status: accepted
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