IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i24p16634-d1295665.html
   My bibliography  Save this article

Research on Hybrid Scheduling of Shared Bikes Based on MLP-GA Method

Author

Listed:
  • Chuanxiang Ren

    (College of Transportation, Shandong University of Science and Technology, Qingdao 266590, China)

  • Hui Xu

    (College of Transportation, Shandong University of Science and Technology, Qingdao 266590, China)

  • Changchang Yin

    (College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China)

  • Liye Zhang

    (College of Transportation, Shandong University of Science and Technology, Qingdao 266590, China)

  • Chunxu Chai

    (College of Transportation, Shandong University of Science and Technology, Qingdao 266590, China)

  • Qiu Meng

    (College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China)

  • Fangfang Fu

    (College of Transportation, Shandong University of Science and Technology, Qingdao 266590, China)

Abstract

Bike-sharing systems with convenience and flexibility have been appearing more and more in cities and become a necessary tool of travel for people. However, the distribution of bikes is highly unbalanced due to the changes in user demand, which leads to the unfavorable situation of “no bikes available” or “too many bikes” at some bike stations. For this reason, this paper proposes a hybrid scheduling method, which combines truck-based scheduling (TBS) and user-based scheduling (UBS). Firstly, a hybrid scheduling model (HBS) combining TBS and UBS is established. Secondly, a method combining multilayer perceptron and genetic algorithm (MLP-GA) is proposed to solve the model. Thirdly, the HBS model is simulated and analyzed by the example. The results show that the MLP-GA method converges, has a faster running time than the genetic algorithm and can obtain solutions with lower total cost and shorter optimal truck path. Further analysis shows that HBS is more implementable in practice and can shorten the optimal truck path and reduce the scheduling total cost while allowing users to use the shared bike in an affordable way, thus realizing the efficient operation of the shared bike system. Finally, a sensitivity analysis of the reward coefficients is performed. This shows that as the reward coefficient increases, the cost of HBS generally shows an increasing trend when the reward coefficient is small, reaches a maximum value when the reward coefficient is 0.6, and decreases slightly thereafter.

Suggested Citation

  • Chuanxiang Ren & Hui Xu & Changchang Yin & Liye Zhang & Chunxu Chai & Qiu Meng & Fangfang Fu, 2023. "Research on Hybrid Scheduling of Shared Bikes Based on MLP-GA Method," Sustainability, MDPI, vol. 15(24), pages 1-23, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16634-:d:1295665
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/24/16634/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/24/16634/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bulhões, Teobaldo & Subramanian, Anand & Erdoğan, Güneş & Laporte, Gilbert, 2018. "The static bike relocation problem with multiple vehicles and visits," European Journal of Operational Research, Elsevier, vol. 264(2), pages 508-523.
    2. Erdoğan, Güneş & Battarra, Maria & Wolfler Calvo, Roberto, 2015. "An exact algorithm for the static rebalancing problem arising in bicycle sharing systems," European Journal of Operational Research, Elsevier, vol. 245(3), pages 667-679.
    3. Shaheen, Susan & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present, and Future," Institute of Transportation Studies, Working Paper Series qt79v822k5, Institute of Transportation Studies, UC Davis.
    4. Haider, Zulqarnain & Nikolaev, Alexander & Kang, Jee Eun & Kwon, Changhyun, 2018. "Inventory rebalancing through pricing in public bike sharing systems," European Journal of Operational Research, Elsevier, vol. 270(1), pages 103-117.
    5. Shaheen, Susan A & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present and Future," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6qg8q6ft, Institute of Transportation Studies, UC Berkeley.
    6. Erdoğan, Güneş & Laporte, Gilbert & Wolfler Calvo, Roberto, 2014. "The static bicycle relocation problem with demand intervals," European Journal of Operational Research, Elsevier, vol. 238(2), pages 451-457.
    7. Forma, Iris A. & Raviv, Tal & Tzur, Michal, 2015. "A 3-step math heuristic for the static repositioning problem in bike-sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 230-247.
    8. Dell'Amico, Mauro & Hadjicostantinou, Eleni & Iori, Manuel & Novellani, Stefano, 2014. "The bike sharing rebalancing problem: Mathematical formulations and benchmark instances," Omega, Elsevier, vol. 45(C), pages 7-19.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carlos M. Vallez & Mario Castro & David Contreras, 2021. "Challenges and Opportunities in Dock-Based Bike-Sharing Rebalancing: A Systematic Review," Sustainability, MDPI, vol. 13(4), pages 1-26, February.
    2. Alain Quilliot & Antoine Sarbinowski & Hélène Toussaint, 2021. "Vehicle driven approaches for non preemptive vehicle relocation with integrated quality criterion in a vehicle sharing system," Annals of Operations Research, Springer, vol. 298(1), pages 445-468, March.
    3. Fu, Chenyi & Zhu, Ning & Ma, Shoufeng & Liu, Ronghui, 2022. "A two-stage robust approach to integrated station location and rebalancing vehicle service design in bike-sharing systems," European Journal of Operational Research, Elsevier, vol. 298(3), pages 915-938.
    4. Du, Mingyang & Cheng, Lin & Li, Xuefeng & Tang, Fang, 2020. "Static rebalancing optimization with considering the collection of malfunctioning bikes in free-floating bike sharing system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    5. Bruno Albert Neumann-Saavedra & Teodor Gabriel Crainic & Bernard Gendron & Dirk Christian Mattfeld & Michael Römer, 2020. "Integrating Resource Management in Service Network Design for Bike-Sharing Systems," Transportation Science, INFORMS, vol. 54(5), pages 1251-1271, September.
    6. Dell’Amico, Mauro & Iori, Manuel & Novellani, Stefano & Subramanian, Anand, 2018. "The Bike sharing Rebalancing Problem with Stochastic Demands," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 362-380.
    7. Huang, Di & Chen, Xinyuan & Liu, Zhiyuan & Lyu, Cheng & Wang, Shuaian & Chen, Xuewu, 2020. "A static bike repositioning model in a hub-and-spoke network framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    8. Ye Ding & Jiantong Zhang & Jiaqing Sun, 2022. "Branch-and-Price-and-Cut for the Heterogeneous Fleet and Multi-Depot Static Bike Rebalancing Problem with Split Load," Sustainability, MDPI, vol. 14(17), pages 1-24, August.
    9. Gilbert Laporte & Frédéric Meunier & Roberto Wolfler Calvo, 2018. "Shared mobility systems: an updated survey," Annals of Operations Research, Springer, vol. 271(1), pages 105-126, December.
    10. Zhang, Yuhan & Shao, Yichang & Bi, Hui & Aoyong, Li & Ye, Zhirui, 2023. "Bike-sharing systems rebalancing considering redistribution proportions: A user-based repositioning approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    11. Lv, Chang & Zhang, Chaoyong & Lian, Kunlei & Ren, Yaping & Meng, Leilei, 2022. "A two-echelon fuzzy clustering based heuristic for large-scale bike sharing repositioning problem," Transportation Research Part B: Methodological, Elsevier, vol. 160(C), pages 54-75.
    12. Xue Bai & Ning Ma & Kwai-Sang Chin, 2022. "Hybrid Heuristic for the Multi-Depot Static Bike Rebalancing and Collection Problem," Mathematics, MDPI, vol. 10(23), pages 1-28, December.
    13. Bulhões, Teobaldo & Subramanian, Anand & Erdoğan, Güneş & Laporte, Gilbert, 2018. "The static bike relocation problem with multiple vehicles and visits," European Journal of Operational Research, Elsevier, vol. 264(2), pages 508-523.
    14. Mohammed Elhenawy & Hesham A. Rakha & Youssef Bichiou & Mahmoud Masoud & Sebastien Glaser & Jack Pinnow & Ahmed Stohy, 2021. "A Feasible Solution for Rebalancing Large-Scale Bike Sharing Systems," Sustainability, MDPI, vol. 13(23), pages 1-19, December.
    15. Lei, Chao & Ouyang, Yanfeng, 2018. "Continuous approximation for demand balancing in solving large-scale one-commodity pickup and delivery problems," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 90-109.
    16. Jiliu Li & Zhixing Luo & Roberto Baldacci & Hu Qin & Zhou Xu, 2023. "A New Exact Algorithm for Single-Commodity Vehicle Routing with Split Pickups and Deliveries," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 31-49, January.
    17. Neumann-Saavedra, Bruno Albert & Mattfeld, Dirk Christian & Hewitt, Mike, 2021. "Assessing the operational impact of tactical planning models for bike-sharing redistribution," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 216-235.
    18. Linfeng Li & Miyuan Shan & Ying Li & Sheng Liang, 2017. "A Dynamic Programming Model for Operation Decision-Making in Bicycle Sharing Systems under a Sustainable Development Perspective," Sustainability, MDPI, vol. 9(6), pages 1-21, June.
    19. Alvarez-Valdes, Ramon & Belenguer, Jose M. & Benavent, Enrique & Bermudez, Jose D. & Muñoz, Facundo & Vercher, Enriqueta & Verdejo, Francisco, 2016. "Optimizing the level of service quality of a bike-sharing system," Omega, Elsevier, vol. 62(C), pages 163-175.
    20. Bruno P. Bruck & Fábio Cruz & Manuel Iori & Anand Subramanian, 2019. "The Static Bike Sharing Rebalancing Problem with Forbidden Temporary Operations," Transportation Science, INFORMS, vol. 53(3), pages 882-896, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16634-:d:1295665. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.