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Vehicle Routing Problem with Drones for Last Mile Delivery
- Source :
- Procedia Manufacturing. 39:314-324
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- E-commerce and retail companies are seeking ways to cut delivery times and costs by exploring opportunities to use drones for making last mile delivery deliveries. In recent years, drone routing and scheduling has become a highly active area of research. This research addresses the delivery concept of a truck-drone combination along with the idea of allowing autonomous drones to fly from delivery trucks, make deliveries, and fly to delivery trucks nearby. The proposed model considers the synchronized truck drone routing model by allowing multiple drones to fly from a truck, serve customers and immediately return to the same truck for the battery swap and package retrieval. The model also takes into account both trucks and drones capacities to ensure that the amount of loads carried by each drone must not exceed its capacity and the total amount of loads in each delivery route must be less than truck’s capacity. The goal is to find the optimal routes of both trucks and drones which minimize the total arrival time of both trucks and drones at the depot after completing the deliveries. The problem can be solved by the formulated mixed integer programming (MIP) for the small size problem. Numerical results in the case study and benchmark problems are presented to show the delivery time improvement over the delivery time from other delivery types.
- Subjects :
- Truck
0209 industrial biotechnology
Operations research
Computer science
ComputerApplications_COMPUTERSINOTHERSYSTEMS
02 engineering and technology
Industrial and Manufacturing Engineering
Drone
Scheduling (computing)
020303 mechanical engineering & transports
020901 industrial engineering & automation
0203 mechanical engineering
Swap (finance)
Artificial Intelligence
Vehicle routing problem
Benchmark (computing)
Routing (electronic design automation)
Integer programming
Subjects
Details
- ISSN :
- 23519789
- Volume :
- 39
- Database :
- OpenAIRE
- Journal :
- Procedia Manufacturing
- Accession number :
- edsair.doi...........c962d8c0a59311c6f4eafb874053edb7