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1.南京邮电大学计算机学院,江苏 南京 210023
2.南京邮电大学江苏省大数据安全与智能处理重点实验室,江苏 南京 210023
[ "徐佳(1980-),男,博士,南京邮电大学教授,主要研究方向为群智感知、无线充电、边缘计算和区块链等。" ]
[ "袁鸣(1997-),女,南京邮电大学计算机学院硕士生,主要研究方向为路径规划和无线充电。" ]
[ "吴思徐(1997-),男,南京邮电大学计算机学院博士生,主要研究方向为无线充电传感器网络。" ]
[ "谭芯(1998-),女,南京邮电大学计算机学院硕士生,主要研究方向为边缘计算。" ]
[ "骆健(1976-),女,南京邮电大学副教授,主要研究方向为数据挖掘和机器学习。" ]
纸质出版日期:2024-06-10,
收稿日期:2023-02-14,
修回日期:2023-09-15,
移动端阅览
徐佳,袁鸣,吴思徐等.一种针对无人机配送网络的能量自维持调度方案[J].物联网学报,2024,08(02):56-70.
XU Jia,YUAN Ming,WU Sixu,et al.An energy self-sustaining scheduling scheme for UAV delivery networks[J].Chinese Journal on Internet of Things,2024,08(02):56-70.
徐佳,袁鸣,吴思徐等.一种针对无人机配送网络的能量自维持调度方案[J].物联网学报,2024,08(02):56-70. DOI: 10.11959/j.issn.2096-3750.2024.00359.
XU Jia,YUAN Ming,WU Sixu,et al.An energy self-sustaining scheduling scheme for UAV delivery networks[J].Chinese Journal on Internet of Things,2024,08(02):56-70. DOI: 10.11959/j.issn.2096-3750.2024.00359.
近年来,快递行业需求快速增长,物流配送行业压力剧增。无人机(UAV
unmanned aerial vehicle)配送凭借其人力成本低、灵活方便等特性成为车辆配送的有益补充。然而,无人机配送受续航能力和负载能力等因素的制约,需要低成本且能量自维持的配送和充电调度方案来支持多无人机的协同配送。提出了两阶段的能量自维持的多无人机协同配送及充电调度方案。第一阶段在满足无人机能量和载重容量约束的前提下,最小化能完成区域内所有配送任务所需的无人机数量,并给出对应配送路线。提出了无人机配送调度算法(UDSA
UAV delivery scheduling algorithm),并从理论上证明了UDSA的近似度。第二阶段对具有不同到达时间的无人机进行充电调度,最小化所有无人机的最大充电完成时间。提出了一种具有近似度的无人机充电调度算法(UCSA
UAV charging scheduling algorithm)来求解该问题。仿真实验结果表明,与基准算法相比,UDSA最多可以减少44.17%的无人机数量;UCSA最多可以缩短18.87%的最大充电完成时间。
In recent years
the demand of express industry has increased rapidly
and the express industry is under increasing pressure. The unmanned aerial vehicle (UAV) delivery has become an effective supplement to vehicle delivery due to its low human cost
flexibility and convenience. However
UAVs are often limited by factors such as endurance and load capacity
requiring a low-cost and energy self-sustaining scheduling scheme for delivery and charging to support collaborative delivery of multiple UAVs. A two-stage self-sustaining multiple UAV cooperative delivery and charging scheduling scheme was proposed. The first stage aims at finding the delivery routes of UAVs to complete all delivery tasks in the region such that the number of UAVs was minimized under the energy and load capacity constraints of UAVs. The UAV delivery scheduling algorithm (UDSA) was proposed
and the approximation of UDSA was proved theoretically. The second stage aims to schedule the charging of UAVs with different arrival times to minimize the maximum charging completion time of all UAVs. An approximate UAV delivery scheduling algorithm (UCSA) was proposed to solve the problem. The simulation results show that
compared with the benchmark algorithm
UDSA can reduce the number of UAVs by 44.17% at most
and UCSA can reduce the maximum charging completion time by 18.87% at most.
无人机配送调度车辆路由问题无线充电调度
UAVdelivery schedulingvehicle routing problemwireless charging scheduling
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