Drone Routing in a Time-Dependent Network: Toward Low-Cost and Large-Range Parcel Delivery

被引:33
作者
Huang, Hailong [1 ]
Savkin, Andrey, V [1 ]
Huang, Chao [2 ]
机构
[1] Univ New South Wales, Sch Elect Engn & Telecommun, Sydney, NSW 2052, Australia
[2] Univ Wollongong, Sch Elect Comp & Telecommun Engn, Wollongong, NSW 2500, Australia
基金
澳大利亚研究理事会;
关键词
Drones; Public transportation; Energy consumption; Trajectory; Batteries; Informatics; Routing; Control of parcel delivery systems; drones; parcel delivery; public transportation network; unmanned aerial vehicles; TRAVELING SALESMAN PROBLEM; OPTIMIZATION;
D O I
10.1109/TII.2020.3012162
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Drones are a promising tool for parcel delivery, since they are cost-efficient and environmentally friendly. However, owing to the limited capacity of the on-board battery, their flight range is constrained. Thus, they cannot deliver some parcels if the customers are too far from the depot. To address this issue, this article proposes a novel method, in which a parcel delivery drone can x201C;takex201D; a public transportation vehicle and travel on its roof. The problem under consideration is how to make use of the public transportation network to route the drone between the depot and the customer. Compared to the currently available methods that use drones, the most important merit of this approach is a significant expansion of the delivery area. We construct a multimodal network consisting of public transportation vehiclesx2019; trips and drone flights. Because of the complexity of this multimodal network, we convert it to a simple network with a set of simple procedures. In the extended network, we formulate the shortest drone path problem that minimizes the return instant to the depot, subject to that the drone energy consumption on this path is no greater than the initial energy. We present a Dijkstra-based method to find the shortest drone path. Moreover, we extend the proposed method to the case with uncertainty, because the public transportation vehicles cannot exactly follow their timetables in practice. Simulation results are presented to demonstrate how the method works.
引用
收藏
页码:1526 / 1534
页数:9
相关论文
共 18 条
[1]   Optimization Approaches for the Traveling Salesman Problem with Drone [J].
Agatz, Niels ;
Bouman, Paul ;
Schmidt, Marie .
TRANSPORTATION SCIENCE, 2018, 52 (04) :965-981
[2]  
Aleksandrov D, 2012, PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE OF DAAAM BALTIC INDUSTRIAL ENGINEERING, VOLS 1 AND 2, P251
[3]   The vehicle routing problem: State of the art classification and review [J].
Braekers, Kris ;
Ramaekers, Katrien ;
Van Nieuwenhuyse, Inneke .
COMPUTERS & INDUSTRIAL ENGINEERING, 2016, 99 :300-313
[4]   Vehicle Routing Problems for Drone Delivery [J].
Dorling, Kevin ;
Heinrichs, Jordan ;
Messier, Geoffrey G. ;
Magierowski, Sebastian .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 47 (01) :70-85
[5]   Ensuring service levels in routing problems with time windows and stochastic travel times [J].
Ehmke, Jan Fabian ;
Campbell, Ann Melissa ;
Urban, Timothy L. .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 240 (02) :539-550
[6]   Models and matheuristics for the unrelated parallel machine scheduling problem with additional resources [J].
Fanjul-Peyro, Luis ;
Perea, Federico ;
Ruiz, Ruben .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2017, 260 (02) :482-493
[7]   Construction heuristics for the asymmetric TSP [J].
Glover, F ;
Gutin, G ;
Yeo, A ;
Zverovich, A .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2001, 129 (03) :555-568
[8]   A range-restricted recharging station coverage model for drone delivery service planning [J].
Hong, Insu ;
Kuby, Michael ;
Murray, Alan T. .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2018, 90 :198-212
[9]   A Method of Optimized Deployment of Charging Stations for Drone Delivery [J].
Huang, Hailong ;
Savkin, Andrey V. .
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2020, 6 (02) :510-518
[10]   A New Parcel Delivery System with Drones and a Public Train [J].
Huang, Hailong ;
Savkin, Andrey, V ;
Huang, Chao .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2020, 100 (3-4) :1341-1354