华南理工大学学报(自然科学版) ›› 2017, Vol. 45 ›› Issue (4): 118-123.doi: 10.3969/j.issn.1000-565X.2017.04.017

• 交通与运输工程 • 上一篇    下一篇

基于双层规划的公共电动自行车租赁点选址模型

胡郁葱1,2 陈枝伟1,2† 黄靖翔1,2   

  1. 1. 华南理工大学 土木与交通学院,广东 广州 510640; 2. 现代城市交通技术江苏高校协同创新中心,江苏 南京 210000
  • 收稿日期:2016-06-06 修回日期:2016-11-04 出版日期:2017-04-25 发布日期:2017-03-01
  • 通信作者: 陈枝伟( 1994-) ,男,主要从事交通运输规划与管理研究. E-mail:1165203662@qq.com
  • 作者简介:胡郁葱( 1970-) ,女,博士,副教授,主要从事交通运输规划与管理研究. E-mail: ychu@ scut. edu. cn
  • 基金资助:

    国家自然科学基金资助项目( 51408237) ; 国家级大学生创新创业训练计划项目( 201510561102)

Location Model for Public Electric Bicycle Rent Based on Bi-Level Programming

HU Yu-cong1,2 CHEN Zhi-wei1,2 HUANG Jing-xiang1,2   

  1. 1.School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,China; 2.Jiangsu Province Collaborative Innovative Center of Modern Urban Traffic Technologies,Nanjing 210000,Jiangsu,China
  • Received:2016-06-06 Revised:2016-11-04 Online:2017-04-25 Published:2017-03-01
  • Contact: 陈枝伟( 1994-) ,男,主要从事交通运输规划与管理研究. E-mail:1165203662@qq.com
  • About author:胡郁葱( 1970-) ,女,博士,副教授,主要从事交通运输规划与管理研究. E-mail: ychu@ scut. edu. cn
  • Supported by:
    Supported by the National Natural Science Foundation of China( 51408237) and the National College Students Innovation and Business Plan( 201510561102)

摘要: 建设公共电动自行车系统是有效利用资源、满足居民经济低碳出行需求的可行途径之一. 文中提出了公共电动自行车网络系统的概念,并采用出行链对其进行分析. 在
此基础上,建立双层规划模型解决该网络系统中的租赁点选址问题. 上层模型考虑政府的目标,为系统最优模型; 下层模型考虑用户的目标,为用户均衡模型. 上层模型采用混合粒子群优化算法求解,下层模型采用Frank-Wolfe 算法求解. 算例结果表明,文中算法能够同时确定站点选址和站点规模,收敛性能较好.

关键词: 公共电动自行车, 选址模型, 双层规划, 混合粒子群优化

Abstract:

Developing public electric bicycle systems is a feasible way to making full use of resources and meeting people's increasing demand for low-carbon trips.This paper first proposes a public electric bicycle network system based on trip chain analysis,and then establishes a bi-level programming model to solve the station location problem of such systems.In this model,the upper part considers the government's goal for system optimization,while the lower part shows respect for system users'interests and user equilibrium.The upper model is solved by using the hybrid particle swarm optimization algorithm and the lower one is solved by using Frank-Wolfe algorithm.Numerical results show that the proposed programming model can determine both the optimal location and the size of stations in the public electric bicycle network system with good convergence.

Key words: public electric bicycle, station location model, bi-level programming, hybrid particle swarm optimization

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