IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i10p4316-d1652606.html

Intelligent Optimization of Bike-Sharing Systems: Predictive Models and Algorithms for Equitable Bicycle Distribution in Barcelona

Author

Listed:
  • Gerard Giner Fabregat

    (Statistics and Operations Research Department, Universitat Politècnica de Catalunya—BarcelonaTech, 08034 Barcelona, Spain
    NTT DATA, 08005 Barcelona, Spain)

  • Pau Fonseca i Casas

    (Statistics and Operations Research Department, Universitat Politècnica de Catalunya—BarcelonaTech, 08034 Barcelona, Spain)

  • Antonio Rivero Martínez

    (NTT DATA, 41092 Sevilla, Spain)

Abstract

This paper aims to propose innovative solutions to improve the management of Barcelona’s bike-sharing system, known as Bicing. This study addresses one of the system’s main challenges: the unequal distribution of bicycles across the city and at different times of the day, which affects the users. The analysis combines advanced statistical techniques, predictive models and optimization algorithms to identify vulnerable areas in terms of accessibility and design strategies to balance bicycle distribution. Using methods such as clustering and predictive models based on machine learning, the system’s usage patterns are anticipated. These predictions feed optimization algorithms that enable the planning of more efficient routes for bicycle repositioning, reducing unnecessary vehicle movement and supporting a more environmentally friendly mobility network. The results highlight the importance of proactive system management, improving both user satisfaction and operational efficiency while fostering a more sustainable urban transport ecosystem.

Suggested Citation

  • Gerard Giner Fabregat & Pau Fonseca i Casas & Antonio Rivero Martínez, 2025. "Intelligent Optimization of Bike-Sharing Systems: Predictive Models and Algorithms for Equitable Bicycle Distribution in Barcelona," Sustainability, MDPI, vol. 17(10), pages 1-33, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4316-:d:1652606
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/10/4316/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/10/4316/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Linwei Hu & Jie Chen & Joel Vaughan & Soroush Aramideh & Hanyu Yang & Kelly Wang & Agus Sudjianto & Vijayan N. Nair, 2021. "Supervised Machine Learning Techniques: An Overview with Applications to Banking," International Statistical Review, International Statistical Institute, vol. 89(3), pages 573-604, December.
    2. Christine Fricker & Nicolas Gast, 2016. "Incentives and redistribution in homogeneous bike-sharing systems with stations of finite capacity," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 5(3), pages 261-291, August.
    3. Zhang, Jie & Meng, Meng & Wong, Yiik Diew & Ieromonachou, Petros & Wang, David Z.W., 2021. "A data-driven dynamic repositioning model in bicycle-sharing systems," International Journal of Production Economics, Elsevier, vol. 231(C).
    4. Rayane El Sibai & Khalil Challita & Jacques Bou Abdo & Jacques Demerjian, 2021. "A New User-Based Incentive Strategy for Improving Bike Sharing Systems’ Performance," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    5. Julio Mario Daza-Escorcia & David Álvarez-Martínez, 2024. "A Matheuristic Approach Based on Variable Neighborhood Search for the Static Repositioning Problem in Station-Based Bike-Sharing Systems," Mathematics, MDPI, vol. 12(22), pages 1-30, November.
    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. Liang, Jiaqi & Jena, Sanjay Dominik & Lodi, Andrea, 2024. "Dynamic rebalancing optimization for bike-sharing systems: A modeling framework and empirical comparison," European Journal of Operational Research, Elsevier, vol. 317(3), pages 875-889.
    2. Shi, Ziyi & Xu, Meng & Song, Yancun & Zhu, Zheng, 2024. "Multi-Platform dynamic game and operation of hybrid Bike-Sharing systems based on reinforcement learning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    3. Yongji Jia & Wang Zeng & Yanting Xing & Dong Yang & Jia Li, 2020. "The Bike-Sharing Rebalancing Problem Considering Multi-Energy Mixed Fleets and Traffic Restrictions," Sustainability, MDPI, vol. 13(1), pages 1-15, December.
    4. J. Christopher Westland & Jian Mou & Dafei Yin, 2018. "Prediction of Shared Bicycle Demand with Wavelet Thresholding," Papers 1802.02683, arXiv.org.
    5. He, Xiaozhou & Wang, Qingyi, 2024. "A stochastic programming model for free-floating shared bike redistribution considering bike gathering," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    6. Yousung Park & Tae Yeon Kwon, 2025. "Ensemble with Divisive Bagging for Feature Selection in Big Data," Computational Economics, Springer;Society for Computational Economics, vol. 66(2), pages 1321-1354, August.
    7. Nicholas Christakis & Dimitris Drikakis, 2023. "Unsupervised Learning of Particles Dispersion," Mathematics, MDPI, vol. 11(17), pages 1-17, August.
    8. Kwiatkowski Michał Adam, 2018. "Urban Cycling as an Indicator of Socio-Economic Innovation and Sustainable Transport," Quaestiones Geographicae, Sciendo, vol. 37(4), pages 23-32, December.
    9. Jiaoe Wang & Jie Huang & Michael Dunford, 2019. "Rethinking the Utility of Public Bicycles: The Development and Challenges of Station-Less Bike Sharing in China," Sustainability, MDPI, vol. 11(6), pages 1-20, March.
    10. Guo, Yuhan & Li, Jinning & Xiao, Linfan & Allaoui, Hamid & Choudhary, Alok & Zhang, Lufang, 2024. "Efficient inventory routing for Bike-Sharing Systems: A combinatorial reinforcement learning framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    11. Caggiani, Leonardo & Camporeale, Rosalia & Marinelli, Mario & Ottomanelli, Michele, 2019. "User satisfaction based model for resource allocation in bike-sharing systems," Transport Policy, Elsevier, vol. 80(C), pages 117-126.
    12. Jaume Torres & Enrique Jiménez-Meroño & Francesc Soriguera, 2024. "Forecasting the Usage of Bike-Sharing Systems through Machine Learning Techniques to Foster Sustainable Urban Mobility," Sustainability, MDPI, vol. 16(16), pages 1-14, August.
    13. Quan-Lin Li & Rui-Na Fan, 2022. "A mean-field matrix-analytic method for bike sharing systems under Markovian environment," Annals of Operations Research, Springer, vol. 309(2), pages 517-551, February.
    14. Xu Zhao & Jie Zhang & Ning Zhang & Yiik Diew Wong & Yufang Zhou & Meng Meng, 2021. "A GIS-CA Model for Planning Bikeways upon the Footpath Network," Sustainability, MDPI, vol. 13(16), pages 1-11, August.
    15. Kou, Zhaoyu & Cai, Hua, 2019. "Understanding bike sharing travel patterns: An analysis of trip data from eight cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 785-797.
    16. Lucietta Guerreiro Martorano & Silvio Brienza Junior & Jose Reinaldo da Silva Cabral de Moraes & Leila Sheila Silva Lisboa & Werlleson Nascimento & Denison Lima Correa & Thiago Martins Santos & Rafael, 2025. "Topoclimatic Zoning of Three Native Amazonian Forest Species: Approach to Sustainable Silviculture," Sustainability, MDPI, vol. 17(4), pages 1-25, February.
    17. Zahra Navidi & Kai Nagel & Stephan Winter, 2020. "Toward identifying the critical mass in spatial two-sided markets," Environment and Planning B, , vol. 47(9), pages 1704-1724, November.
    18. Cheng, Yao & Wang, Junwei & Wang, Yan, 2021. "A user-based bike rebalancing strategy for free-floating bike sharing systems: A bidding model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    19. 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.
    20. Jara-Díaz, Sergio & Latournerie, André & Tirachini, Alejandro & Quitral, Félix, 2022. "Optimal pricing and design of station-based bike-sharing systems: A microeconomic model," Economics of Transportation, Elsevier, vol. 31(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:17:y:2025:i:10:p:4316-:d:1652606. 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.