部分充电策略下电动车-无人机协同配送路径优化  

Optimization of electric vehicle-drone collaborative delivery path by partial charging strategy

作　　者：陈诚[1] 罗泽龙 杜帅举 纪晓燕 应晨阳 吴杭玲 CHEN Cheng;LUO Zelong;DU Shuaiju;JI Xiaoyan;YING Chenyang;WU Hangling(College of Transportation and Civil Engineering,Fujian Agriculture and Forestry University,Fuzhou 350002,China)

机构地区：[1]交通与土木工程学院,福建农林大学,福建福州350002

出　　处：《长沙理工大学学报(自然科学版)》2025年第1期142-153,共12页Journal of Changsha University of Science & Technology:Natural Science

基　　金：福建省自然科学基金资助项目(2023J01474);国家社会科学基金资助项目(22BGL005);国家级大学生创新创业训练项目(202410389033);福建农林大学校级大学生创新创业训练项目(202410389368)。

摘　　要：【目的】为提升农村物流配送效率和服务水平,建立绿色可持续的农村物流配送模式,研究部分充电策略下有时间窗的电动车-无人机绿色配送路径优化问题。【方法】首先,以电动车和无人机的固定成本、行驶成本、充电成本和碳排放成本构成的总配送成本最小化为目标,构建路径优化数学模型。然后,针对问题特点设计了基于大邻域搜索算法和变邻域下降算法的混合算法并进行求解。最后,通过数值分析试验,验证了模型的合理性和算法的有效性。【结果】对不同配送模式的配送成本及其组成进行对比发现:在配送网络中纳入充电站节点能使总成本降低14.97%,引入无人机协同配送能使总成本降低35.25%,而同时引入充电站和无人机能实现42.03%的成本节省。对电动车和无人机电池容量进行敏感性分析发现:加大电动车电池容量能显著降低总配送成本,主要体现在途中充电绕行里程的减少上;随着无人机电池容量的增大,无人机服务客户数也会增加,从而提高了配送效率,降低了电动车行驶成本、充电成本以及碳排放成本。【结论】本研究成果能为农村电动车-无人机协同配送路径优化决策及低碳可持续性农村物流配送体系的构建提供理论参考。[Purposes]To enhance the delivery efficiency and service quality of logistics in rural areas and establish a green and sustainable delivery mode of logistics in rural areas,this study focused on the electric vehicle-drone green delivery path optimization problem with time windows and partial charging strategy.[Methods]First,a mathematical model for path optimization was formulated with the objective of minimizing the total delivery cost comprising fixed costs,travel costs,charging costs,and carbon emissions associated with electric vehicles and drones.Second,a hybrid algorithm was proposed considering the characteristics of the problem,which integrated a large neighborhood search algorithm with a variable neighborhood descent algorithm.Finally,numerical experiments were conducted to validate both the rationality of the mathematical model and the effectiveness of the proposed algorithm.[Findings]The comparison of the total costs and their individual components across different delivery modes shows that incorporating charging station nodes into the delivery network brings a reduction of 14.97% in the total cost,and adopting drone collaborative delivery brings a total cost reduction of 35.25%.In addition,a cost savings of 42.03% is achieved when charging stations and drone delivery are both implemented.Moreover,sensitivity analyses on the battery capacity for both electric vehicles and drones unveil that improving the battery capacity of electric vehicles results in the reduction of detours for charging and then a decrease in the total delivery cost.As the drone’s battery capacity increases,the number of customers served by drones increases.Consequently,delivery efficiency is improved,and the travel cost,charging cost,and carbon emission cost are decreased.[Conclusions]These findings provide theoretical references for the optimization of the electric vehicle-drone collaborative delivery path in rural areas and the construction of a low-carbon and sustainable rural logistics delivery system.

关 键 词：农村物流 电动车-无人机协同配送 部分充电策略 混合启发式算法 碳排放 时间窗 

分 类 号：U492.3[交通运输工程—交通运输规划与管理] F252[交通运输工程—道路与铁道工程]