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山东大学学报 (工学版) ›› 2024, Vol. 54 ›› Issue (2): 47-59.doi: 10.6040/j.issn.1672-3961.0.2023.022

• 交通运输工程—智慧交通专题 • 上一篇    

基于排队模型的电动物流车充电站选址和运输路径问题

赵姣1,杨倩倩2,胡大伟1,胡卉1,李洋3   

  1. 1.长安大学运输工程学院, 陕西 西安 710064;2.北京布瑞知识产权代理有限公司, 北京100000;3.中交第一公路勘察设计研究院有限公司, 陕西 西安 710064
  • 发布日期:2024-04-17
  • 作者简介:赵姣(1983— ), 女, 辽宁沈阳人, 讲师, 博士, 主要研究方向为智慧交通. E-mail:jiaozhao@chd.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(72274024);陕西省重点研发计划项目(2021GY-184)

Charging station location and transportation routing problem of electric logistics vehicles based on queuing model

ZHAO Jiao1, YANG Qianqian2, HU Dawei1, HU Hui1, LI Yang3   

  1. 1. School of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China;
    2. Beijing Burui Intellectual Property Agency Co., Ltd., Beijing 100000, China;
    3. CCCC First Highway Consultants Co., Ltd., Xi'an 710064, Shaanxi, China
  • Published:2024-04-17

摘要: 针对电动物流车辆规模化应用中电池容量小和充电时间长的问题,以充电站选址和运输路径集成优化为目标,考虑因充电排队等待因素及电动车能耗碳排放成本,建立带时间窗的电动物流车选址-路径问题(location-routing problem, LRP)模型。基于遗传算法,加入贪婪搜索策略、精英保留策略和劣解突变策略求解模型。针对小规模测试算例,采用LINGO优化求解器与改进的遗传算法进行求解效果分析,验证算法的有效性;采用较大规模不同分布的测试数据进行分析计算后,改进的遗传算法比传统的遗传算法平均改进54.52%,表明改进遗传算法能够较大程度改进求解能力。分析充电站服务率参数对各项成本的影响,发现随着充电站服务率的增加,总成本整体呈下降趋势,表明所提模型更加符合实际,为电动物流车大规模推广应用提供了理论依据。

关键词: 电动物流车, 选址路径问题, 排队时间, 遗传算法, 贪婪搜索

中图分类号: 

  • U116
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