Cooperative route planning for the drone and truck in delivery services: A bi-objective optimisation approach

被引:50
|
作者
Wang, Kangzhou [1 ]
Yuan, Biao [2 ]
Zhao, Mengting [3 ]
Lu, Yuwei [4 ]
机构
[1] Lanzhou Univ, Sch Management, Lanzhou, Gansu, Peoples R China
[2] SAIC Motor Artificial Intelligence Lab, Shanghai, Peoples R China
[3] Wuhan Univ Sci & Technol, Sch Automobile & Traff Engn, Wuhan, Hubei, Peoples R China
[4] Guangxi Univ Sci & Technol, Sch Mech & Transportat Engn, Liuzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Logistics; travelling salesman problem; multi-objective optimisation; drone-assisted delivery; metaheuristics; TRAVELING SALESMAN PROBLEM; EVOLUTIONARY ALGORITHM;
D O I
10.1080/01605682.2019.1621671
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
The deployment of drones to support the last-mile delivery has been initially attempted by several companies such as Amazon and Alibaba. The complementary capabilities of the drone and the truck pose an innovative delivery mode. The relevant optimisation problem associated with this new mode, known as the travelling salesman problem with drone (TSP-D), aims to find the coordinated routes of a drone and a truck to serve a list of customers. In practice, managers sometimes intend to attain a compromise between operational cost and completion time. Therefore, this article addresses a bi-objective TSP-D considering both objectives. An improved non-dominated sorting genetic algorithm (INSGA-II) is proposed to solve the problem. Specifically, the label algorithm-based decoding method, the fast non-dominated sorting approach, the crowding-distance computation procedure, and the local search component are devised to accommodate the features of the problem. Furthermore, the first Pareto front obtained by the INSGA-II is improved by a post-optimisation component. Computational results validate the competitive performance of the proposed algorithm. Meanwhile, the trade-off analysis demonstrates the relationship between operational cost and completion time and provides managerial insights for managers designing reasonable compromise routes.
引用
收藏
页码:1657 / 1674
页数:18
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