Hybrid rebalancing with dynamic hubbing for free-floating bike sharing systems

被引:8
|
作者
Mahmoodian, Vahid [1 ]
Zhang, Yu [2 ]
Charkhgard, Hadi [1 ]
机构
[1] Univ S Florida, Dept Ind & Management Syst Engn, Tampa, FL 33620 USA
[2] Univ S Florida, Dept Civil & Environm Engn, Tampa, FL 33620 USA
关键词
Hub -based rebalancing; User incentive program; Free-floating bike sharing; Simulation; Multi -objective optimization; VEHICLE; FRAMEWORK; NETWORK; RELOCATION; DEMAND;
D O I
10.1016/j.ijtst.2021.08.002
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
For managing the supply-demand imbalance in free-floating bike sharing systems, we propose dynamic hubbing (i.e., geofencing areas varying from one day to another) and hybrid rebalancing (combining user-based and operator-based strategies) and solve the problem with a novel multi-objective simulation optimization approach. Given historical usage data and real-time bike GPS location information, the basic concept is that dynamic hubs are determined to encourage users to return bikes to desired areas towards the end of the day through a user incentive program. Then, for the remaining unbalanced bikes, an operator-based rebalancing operation will be scheduled. The proposed modeling and optimization solution algorithm determines the number of hubs, their locations, the start time for initiating the user incentive program, and the amount of incentive by considering two conflicting objectives, i.e., level of service and rebalancing cost. In this study, for freefloating bike sharing, the level of service is represented by the walking distance of users for locating a usable bike, which is different from level of service metrics commonly used by station-based bike sharing, and the rebalancing cost is weighted incentive credits plus operator-based rebalancing cost. We implemented the proposed method on the Share-ABull free-floating bike sharing system at the University of South Florida. Results show that a hybrid rebalancing and dynamic hubbing strategy can significantly reduce the total rebalancing cost and improve the level of service. Moreover, taking the advantage of crowdsourcing (or job-sharing) reduces negative impacts-energy consumption and greenhouse gas emissions-of the operation of rebalancing vehicles and makes bike sharing a more promising environmentally friendly sharing transportation mode.& COPY; 2021 Tongji University and Tongji University Press. Publishing Services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
引用
收藏
页码:636 / 652
页数:17
相关论文
共 50 条
  • [1] Dynamic Rebalancing of the Free-Floating Bike-Sharing System
    Zhang, Wenbin
    Niu, Xiaolei
    Zhang, Guangyong
    Tian, Lixin
    [J]. SUSTAINABILITY, 2022, 14 (20)
  • [2] A multiobjective dynamic rebalancing evolutionary algorithm for free-floating bike sharing
    Su, Sheng
    Yu, Haijie
    Xiong, Dongwen
    Dong, Xiaohua
    [J]. APPLIED SOFT COMPUTING, 2023, 147
  • [3] A Rolling-Horizon Strategy for Dynamic Rebalancing of Free-Floating Bike-Sharing Systems
    Chen, Dawei
    Chen, Qun
    Imdahl, Christina
    Woensel, Tom Van
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (11) : 12123 - 12140
  • [4] A Cluster-Then-Route Framework for Bike Rebalancing in Free-Floating Bike-Sharing Systems
    Sun, Jiaqing
    He, Yulin
    Zhang, Jiantong
    [J]. SUSTAINABILITY, 2023, 15 (22)
  • [5] A user-based bike rebalancing strategy for free-floating bike sharing systems: A bidding model
    Cheng, Yao
    Wang, Junwei
    Wang, Yan
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2021, 154
  • [6] Optimizing bike rebalancing strategies in free-floating bike-sharing systems: An enhanced distributionally robust approach
    Chen, Qingxin
    Ma, Shoufeng
    Li, Hongming
    Zhu, Ning
    He, Qiao-Chu
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2024, 184
  • [7] A modeling framework for the dynamic management of free-floating bike-sharing systems
    Caggiani, Leonardo
    Camporeale, Rosalia
    Ottomanelli, Michele
    Szeto, Wai Yuen
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2018, 87 : 159 - 182
  • [8] A two-stage incentive mechanism for rebalancing free-floating bike sharing systems: Considering user preference
    Wang, Junwei
    Wang, Yan
    [J]. TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2021, 82 : 54 - 69
  • [9] Static rebalancing optimization with considering the collection of malfunctioning bikes in free-floating bike sharing system
    Du, Mingyang
    Cheng, Lin
    Li, Xuefeng
    Tang, Fang
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2020, 141
  • [10] Optimization of Free-Floating Bike Sharing Systems: Considerations in Recovery of Damaged Bicycles
    Qiao, Rui
    Zhou, Yiyan
    [J]. CICTP 2020: TRANSPORTATION EVOLUTION IMPACTING FUTURE MOBILITY, 2020, : 2362 - 2374