Two-Echelon Routing Problem for Parcel Delivery by Cooperated Truck and Drone

Abstract

A new variant of two-echelon routing problem is investigated, where the truck and the drone are used to cooperatively complete the deliveries of all parcels. The truck not only acts as a tool for parcel delivery, but also serves as a moving depot for the drone. The drone can carry several parcels and take off from the truck, while returning to the truck after completing the delivery. The energy consumption model for the routing process of the drone is analyzed, when it is utilized to deliver multiple parcels. A two-stage route-based modelling approach is proposed to optimize both the truck’s main route and the drone’s adjoint flying routes. A hybrid heuristic integrating nearest neighbor and cost saving strategies is developed to quickly construct a feasible solution. The simulated annealing algorithm is applied to improve the quality of the solution, where a Tabu list is employed to improve the search efficiency. Random instances at different scales are used to test the performance of the proposed algorithm. A case study based on the practical road network in Changsha, China, is presented, through which the sensitivity analysis is conducted with respect to some critical factors.

Last-mile delivery concepts: a survey from an operational research perspective

“…Drones can, thus, visit more than a single customer before returning to the truck. Very similar problem settings are considered by Kitjacharoenchai et al (2020) and Liu et al (2020). The peculiarities of pickup and delivery jobs operated by truck-and-drone tandems are investigated by Karak and Abdelghany (2019).…”

Trucks and drones cooperation in the last‐mile delivery process

“…Kitjacharoenchai et al [26] and Liu et al [31] propose a variant of the classical VRP-D, named two-echelon VRP-D, where the delivery process with trucks and drones is modeled as a two-level delivery system. The first level is the routing of the trucks from the main depot to customers, the second one the routing of drones from truck to customers.…”

“…The authors propose two heuristics to solve the problem, the first one based on a construction algorithm and the second one on large neighborhood search. Liu et al [31] calculate the energy consumption of drones battery, by considering an energy consumption model which takes into account several parameters such as the payload, the distance traveled, and the flying speed (assumed to be constant). They propose a heuristic based on nearest neighborhoods and savings algorithms.…”

“…In the majority of the works, the main objective is to reduce the overall time to perform the deliveries and to improve the quality of service at the same time. Only few works, considering a mixed fleet, analyze the benefits in terms of costs (see [5,8,10,31,42,45,54]) and the limited capacity of trucks (see [5,8,10,31,42,45,53,54]). However, the majority of the works do not consider time window constraints.…”

Biased Random-key Genetic Algorithm for theHybrid Vehicle-drone Routing Problem for Pick-upand Delivery

“…This tendency will continue to grow significantly due to several contributing factors: the continued expansion of online retail, high competition for pick-up and delivery service providers, and drones' improved capabilities and cost-effectiveness. The HVDRP provides a problem model that differs from other systems that use a single drone, like Flying Sidekick Traveling Salesman Problem [17], and the Two-Echelon Vehicle Routing Problem [21], [22], [23].…”