Multimodal transport distribution model for autonomous driving vehicles based on improved ALNS

被引:9
|
作者
Guo, Yanhong [1 ]
Chen, Xinxin [1 ]
Yang, Yanyan [1 ]
机构
[1] Dalian Univ Technol, Sch Econ & Management, Dalian 116000, Peoples R China
关键词
Automated driving vehicles; Multimodal transport; Vehicle routing problem; Adaptive large neighborhood search; ROUTING PROBLEMS; LOCAL SEARCH; SOLVE;
D O I
10.1016/j.aej.2021.08.029
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Automated driving technology is one of the emerging technologies which will change the transportation mode in the future. Distributing the automated driving vehicles from the automobile factory to dealers has a huge difference compared with traditional vehicles. This paper considers the variety of cases where the automated driving vehicles can be both distribution tools and distribution goods. Then establishes a new distribution model that integrates self-distribution of autonomous vehicles into the existing distribution rings form a complex network composed of ring-branches. This cooperative distribution model of automated driving and traditional vehicle transport to minimize transportation cost and maximize the overall efficiency. Furthermore, we design an improved adaptive large neighborhood algorithm (ALNS) to solve the model which combines the merger heuristics and splitter heuristics to promote generate the optimal solutions. The efficiency of our proposed method is proved by real-world data from an automobile enterprise. Additionally, the sensitivity analysis of the maximum distance for automated driving vehicles to be delivered by themselves suggests that the larger distance, the more outstanding of cost reduction and efficiency increase for our proposed model. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.
引用
收藏
页码:2939 / 2958
页数:20
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