A GRASP Approach for the Energy-Minimizing Electric Vehicle Routing Problem with Drones

被引:1
|
作者
Kyriakakis, Nikolaos A. [1 ]
Stamadianos, Themistoklis [1 ]
Marinaki, Magdalene [1 ]
Marinakis, Yannis [1 ]
机构
[1] Tech Univ Crete, Sch Prod Engn & Management, Khania 73100, Greece
来源
WORLD ELECTRIC VEHICLE JOURNAL | 2023年 / 14卷 / 12期
关键词
drones; electric vehicle; unmanned aerial vehicle routing; GRASP; TRAVELING SALESMAN PROBLEM; TIME WINDOWS; OPTIMIZATION MODEL; PATH RELINKING; DELIVERY; STATIONS;
D O I
10.3390/wevj14120354
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This study addresses the Electric Vehicle Routing Problem with Drones (EVRPD) by implementing and comparing two variants of the Greedy Randomized Adaptive Search Procedure (GRASP). The primary objective of the EVRPD is to optimize the routing of a combined fleet of ground and aerial vehicles, with the aim of improving delivery efficiency and minimizing energy consumption, which is directly influenced by the weight of the packages. The study assumes a standardized packing system consisting of three weight classes, where deliveries are exclusively performed by drones, while ground vehicles function as mobile depots. The two employed GRASP variants vary in their methods of generating the Restricted Candidate List (RCL), with one utilizing a cardinality-based RCL and the other adopting a value-based RCL. To evaluate their performance, benchmark instances from the existing EVRPD literature are utilized, extensive computational experiments are conducted, and the obtained computational results are compared and discussed. The findings of the research highlight the considerable impact of RCL generation strategies on solution quality. Lastly, the study reports four new best-known values.
引用
收藏
页数:21
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