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作 者:曹卓 王鑫鑫[1] 徐仟 马云峰[1] CAO Zhuo;WANG Xinxin;XU Qian;MA Yunfeng(School of Management,Wuhan University of Science and Technology,Wuhan 430065,China)
出 处:《物流科技》2023年第15期26-30,共5页Logistics Sci-Tech
基 金:湖北省高校哲社重大课题项目(19ZD015);中国物流学会研究课题项目(2022CSLKT3-336)。
摘 要:考虑到电动车在当今物流配送环节中扮演着愈发重要的角色,电动车物流配送过程中充电站位置选择、充电时机选择以及相应路径规划越来越成为行业内备受关注的问题。文章基于车联网对电动车物流配送路径优化进行研究。首先,借助车联网技术获取实时交通路况以及充电站相关信息,提出车联网情境下基于排队论的充电排队等待时间预测模型。其次,考虑时间、路径选择、电量及载重约束,构建以参与配送车辆的配送时间成本、耗电成本以及时间窗惩罚成本之和最优为目标的电动车物流配送路径优化模型。最后通过算例验证模型的可行性以及算法的有效性。实验结果表明相较于最迟充电策略下的电动车物流配送路径优化模型,基于车联网的电动车物流配送路径优化模型具有显著优势。Considering that electric vehicles play an increasingly important role in today's logistics distribution,the selection of charging station location,charging timing and the corresponding path planning in the logistics distribution of electric vehicles has become an increasingly concerned issue in the industry.Based on the internet of vehicles,this paper studies the optimization of logistics distribution route for electric vehicles.Firstly,the real-time traffic conditions and related information of charging stations were obtained by means of the internet of vehicles technology,and a charging queue waiting time prediction model based on the queuing theory was proposed under the internet of vehicles technology scenario.Secondly,considering the constraints of time,path selection,electric quantity and load,an optimization model of logistics distribution route for electric vehicles was established with the goal of optimizing the sum of distribution time cost,power consumption cost and time window penalty cost of participating vehicles.Finally,an example is given to verify the feasibility of the model and the effectiveness of the algorithm.The experimental results show that compared with the logistics distribution path optimization model of EV based on the latest charging strategy,the logistics distribution path optimization model of EV based on the internet of vehicles has significant advantages.
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