Abstract
This work focuses on the optimization of a last-mile delivery system with multiple transportation modes. In this scenario, parcels need to be delivered to each customer point. The major feature of the problem is the combination of a fleet of road vehicles (vans) with a drone. Each van visits a subset of demand nodes to be determined according to the route of the van. The drone serves the customers not served by vans. At the same time, considering the safety, policy and terrain as well as the need to replace the battery, the drone needs to be transported by truck to the identified station along with the parcel. From each such station, the drone serves a subset of customers according to a direct assignment pattern, i.e., every time the drone is launched, it serves one demand node and returns to the station to collect another parcel. Similarly, the truck is used to transport the drone and cargo between stations. This is somewhat different from the research of other scholars. In terms of the joint distribution of the drone and road vehicle, most scholars will choose the combination of two transportation tools, while we use three. The drone and vans are responsible for distribution services, and the trucks are responsible for transporting the goods and drone to the station. The goal is to optimize the total delivery cost which includes the transportation costs for the vans and the delivery cost for the drone. A fixed cost is also considered for each drone parking site corresponding to the cost of positioning the drone and using the drone station. A discrete optimization model is presented for the problem in addition to a two-phase heuristic algorithm. The results of a series of computational tests performed to assess the applicability of the model and the efficiency of the heuristic are reported. The results obtained show that nearly 10% of the cost can be saved by combining the traditional delivery mode with the use of a drone and drone stations.
Highlights
The study of operations research models and methods for problems involving unmanned aerial vehicles (UAVs) has become quite popular in the second decade of the 2000 s
The main contributions of this paper include: (1) a new logistics distribution model in which using a drone is proposed and a numerical analysis shows that this distribution model is more efficient in cost; (2) for this distribution model, we propose an integer programming model called multiple TSP (mTSP)-LAP; (3) for the mTSP-LAP model, we designed a two-stage heuristic algorithm to solve it
We recall the decisions we consider in our mTSP-LAP: (i) the delivery mode used to serve each demand node; (ii) the routes for road delivery; (iii) the stations used to park the truck as well as release and recover the drone; and (iv) the demand nodes to be served from each drone station
Summary
The study of operations research models and methods for problems involving unmanned aerial vehicles (UAVs) has become quite popular in the second decade of the 2000 s. We recently observed technological developments motivating the study of problems such as the one we are considering: the industry has conceived vehicles that can carry a drone and act as drone dock-stations to position a drone in a more convenient location for supplying a set of delivery orders. This is the case with the new ”vans and drones” concept launched by Mercedes-Benz in which the roof of a van is used as a landing platform for drones (https://www.mercedes-benz.com/en/vehicles/transporter/vansdrones-in-zurich/, accessed on 1 March 2020). The paper ends with an overview of the work achieved
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