计算机集成制造系统 ›› 2023, Vol. 29 ›› Issue (5): 1747-1757.DOI: 10.13196/j.cims.2023.05.029

• • 上一篇    下一篇

基于自适应聚类的共享单车需求预测与投放决策

郭洪飞1,2,赵淑曼3,任亚平1,2+,张超勇4   

  1. 1.暨南大学物联网与物流工程研究院
    2.暨南大学智能科学与工程学院
    3.暨南大学管理学院
    4.华中科技大学数字制造装备与技术国家重点实验室
  • 出版日期:2023-05-31 发布日期:2023-06-15
  • 基金资助:
    国家自然科学基金资助项目(51875251);广州市科技计划资助项目(202002030321);广东省研究生教育创新计划资助项目(82620516);广东省基础与应用基础研究基金联合基金青年基金资助项目(2019A1515110399);广东省高等教育教学研究和改革资助项目(2020059);广东省学位与研究生教育改革研究资助项目(2019JGXM15);广州市创新领军团队资助项目(201909010006);暨南大学大学生校外实践教学基地建设资助项目(55691207);暨南大学研究生教育教学成果培育资助项目(2021YPY010);内蒙古科技创新引导资助项目(2022CXYD001)。

Demand prediction and allocation approach of bike-sharing stations based on adaptive clustering

GUO Hongfei1,2,ZHAO Shuman3,REN Yaping1,2+,ZHANG Chaoyong4   

  1. 1.Institute of Physical Internet,Jinan University
    2.School of Intelligent Systems Science and Engineering,Jinan University
    3.School of Management,Jinan University
    4.State Key Laboratory of Digital Manufacturing Equipment and Technology,Huazhong University of Science and Technology
  • Online:2023-05-31 Published:2023-06-15
  • Supported by:
    Project supported by the Social Natural Science Foundation,China(No.51875251),the Funds for Science and Technology Plan  in Guangzhou City,China(No.202002030321),the Guangdong Provincial Graduate Education Innovation Program,China(No.82620516),the Basic and Applied Basic Research Foundation of Guangdong Province,China(No.2019A1515110399),the Guangdong Provincial Higher Education Teaching Research and Reform Program,China(No.2020059),the Guangdong Provincial Academic Degree and Graduate Education Reform Research Program,China(No.2019JGXM15),the Guangzhou Leading Innovation Team Program,China(No.201909010006),the Jinan University Off-Campus Practice Teaching Base Construction Foundation,China(No.55691207),the Jinan University Graduate Education and Teaching Achievement Cultivation Program,China(No.2021YPY010),and the Inner Mongolia Science and Technology Innovation Guide Program,China(No.2022CXYD001).

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摘要： 为了解决有桩共享单车系统(BSS)发生站点失衡导致用户不满和真实需求失真的问题,提出一种基于自适应聚类的站点借还车需求预测和投放量决策方法。首先基于XGBoost原理将站点聚类,然后依次在类层次和站点层次估计借还车需求量,考虑导致需求失真的两种场景,最后根据各站点各时段需求量的预测结果多次模拟系统服务过程,以被拒需求数量的期望值为指标计算各站点以客户满意为导向的最优投放量。论文以纽约CitiBike系统为例进行分析,总结了运营建议,并设计对比试验验证了所提方法对捕捉BSS潜在需求并提高服务率的有效性。

关键词: 共享单车系统, 需求预测, 需求失真, 站点聚类, XGBoost算法, 最优投放量

Abstract: To solve the problem of user dissatisfaction and demand distortion caused by the imbalance of docked Bike-Sharing System (BSS),a station demand prediction and allocation method based on adaptive clustering was proposed.Stations in BSS were clustered according to the principle of XGBoost first,and then the demand of regions and stations were estimated in turn considering the two situations that leaded to demand distortion.The system service process was simulated many times according to the prediction results of the withdraw/return demand of each station in each period of time to get the optimal value of initial inventory at each station which met the most customer needs on average.The CitiBike system in New York was taken as an example to make an analysis,the operation suggestions was summarized and a comparative experiment was designed to verify the effectiveness of the proposed method for capturing the potential demand of BSS and improving the service capacity.

Key words: bike-sharing systems, demand prediction, demand distortion, site clustering, XGBoost algorithm, optimal initial inventory

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