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Multi-Platform dynamic game and operation of hybrid Bike-Sharing systems based on reinforcement learning

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  • Shi, Ziyi
  • Xu, Meng
  • Song, Yancun
  • Zhu, Zheng

Abstract

The advent of electric bikes, or ebikes, has significantly enhanced competitiveness of bike-sharing systems, providing benefits to both riders (comfort during uphill and long-distance rides), platforms (more profit), and the environment. Operating such a hybrid bike-sharing system, i.e., with both bikes and ebikes, in a competitive multi-platform market, can be challenging due to the complex and unpredictable interplay among heterogeneous market participants, which becomes more pronounced with the ebike varying battery, and dynamic demand. Most related research is predicated on the assumption of a monopoly market, which is not always the case: in worldwide capital-oriented markets, many firms will quickly imitate and join in rapidly developing fields for profits. Thus, this paper addresses platforms’ hybrid bike-sharing system operation problem with time-varying ebike pricing and rebalancing strategy in consideration of competition. We consider two docked hybrid bike-sharing platforms with charging stations at the site. Platforms utilize trucks for their own rebalancing operation including bike, ebike and mixed bike/ebike relocation tasks. We combine the Markov decision process (MDP) model with game theory, and establish the dual-platform MDP framework in which one mainstream platform and one competing platform optimize their profits by dynamic pricing and bike/ebike rebalancing based on highly dynamic and stochastic demand. Users’ choice is described by a modified nested logit model and the endogenous demand is generated. We develop the tailored double dueling deep Q-network for solving dynamic gaming. A series of experiments are conducted based on the real-world dataset in Shenzhen and several strategy combinations are compared. The results show the win–win situation where both platforms improve profits with a higher market ratio and demonstrate how to introduce and operate ebikes in the system by analyzing detailed strategies in different games.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:transe:v:181:y:2024:i:c:s1366554523003629
    DOI: 10.1016/j.tre.2023.103374
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    References listed on IDEAS

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    1. Gautham Ram Chandra Mouli & Peter Van Duijsen & Francesca Grazian & Ajay Jamodkar & Pavol Bauer & Olindo Isabella, 2020. "Sustainable E-Bike Charging Station That Enables AC, DC and Wireless Charging from Solar Energy," Energies, MDPI, vol. 13(14), pages 1-21, July.
    2. Tang, Wei & Xie, Ningke & Mo, Dong & Cai, Zeen & Lee, Der-Horng & Chen, Xiqun (Michael), 2023. "Optimizing subsidy strategies of the ride-sourcing platform under government regulation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    3. Fu, Chenyi & Ma, Shoufeng & Zhu, Ning & He, Qiao-Chu & Yang, Hai, 2022. "Bike-sharing inventory management for market expansion," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 28-54.
    4. 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.
    5. Zhang, J. & Meng, M. & Wang, David, Z.W., 2019. "A dynamic pricing scheme with negative prices in dockless bike sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 201-224.
    6. Ke, Jintao & Li, Xinwei & Yang, Hai & Yin, Yafeng, 2021. "Pareto-efficient solutions and regulations of congested ride-sourcing markets with heterogeneous demand and supply," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    7. Mo, Dong & Yu, Jingru & Chen, Xiqun Michael, 2020. "Modeling and managing heterogeneous ride-sourcing platforms with government subsidies on electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 447-472.
    8. Liu, Yixiao & Tian, Zihao & Pan, Baoran & Zhang, Wenbin & Liu, Yunqi & Tian, Lixin, 2022. "A hybrid big-data-based and tolerance-based method to estimate environmental benefits of electric bike sharing," Applied Energy, Elsevier, vol. 315(C).
    9. Lazarus, Jessica & Pourquier, Jean Carpentier & Feng, Frank & Hammel, Henry & Shaheen, Susan, 2020. "Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt96g9c9nd, Institute of Transportation Studies, UC Berkeley.
    10. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2020. "Artificial Intelligence, Algorithmic Pricing, and Collusion," American Economic Review, American Economic Association, vol. 110(10), pages 3267-3297, October.
    11. Zhu, Zheng & Ke, Jintao & Wang, Hai, 2021. "A mean-field Markov decision process model for spatial-temporal subsidies in ride-sourcing markets," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 540-565.
    12. 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.
    13. Guangyu Cao & Ginger Zhe Jin & Xi Weng & Li‐An Zhou, 2021. "Market‐expanding or Market‐stealing? Competition with network effects in bike‐sharing," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 778-814, December.
    14. Schuijbroek, J. & Hampshire, R.C. & van Hoeve, W.-J., 2017. "Inventory rebalancing and vehicle routing in bike sharing systems," European Journal of Operational Research, Elsevier, vol. 257(3), pages 992-1004.
    15. Ke, Jintao & Cen, Xuekai & Yang, Hai & Chen, Xiqun & Ye, Jieping, 2019. "Modelling drivers’ working and recharging schedules in a ride-sourcing market with electric vehicles and gasoline vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 160-180.
    16. Jason R. Blevins & Ahmed Khwaja & Nathan Yang, 2018. "Firm Expansion, Size Spillovers, and Market Dominance in Retail Chain Dynamics," Management Science, INFORMS, vol. 64(9), pages 4070-4093.
    17. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    18. Zhu, Zheng & Xu, Ailing & He, Qiao-Chu & Yang, Hai, 2021. "Competition between the transportation network company and the government with subsidies to public transit riders," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    19. Liang Guo, 2006. "Consumption Flexibility, Product Configuration, and Market Competition," Marketing Science, INFORMS, vol. 25(2), pages 116-130, 03-04.
    20. Dong, Zhongpeng & Fan, Zhi-Ping & Wang, Ningning, 2023. "An analysis of pricing strategy for bike-sharing services: The role of the inconvenience cost," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    21. Zhiwei Chen & Yucong Hu & Jutint Li & Xing Wu, 2020. "Optimal Deployment of Electric Bicycle Sharing Stations: Model Formulation and Solution Technique," Networks and Spatial Economics, Springer, vol. 20(1), pages 99-136, March.
    22. Jiang, Zhoutong & Lei, Chao & Ouyang, Yanfeng, 2020. "Optimal investment and management of shared bikes in a competitive market," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 143-155.
    23. Fitch, Dillon & Mohiuddin, Hossain & Handy, Susan, 2020. "Electric Bike-share in the Sacramento Region is Replacing Car Trips and Supporting More Favorable Attitudes Towards Bicycling," Institute of Transportation Studies, Working Paper Series qt8gm3w9qp, Institute of Transportation Studies, UC Davis.
    24. 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.
    25. Ke, Jintao & Zhu, Zheng & Yang, Hai & He, Qiaochu, 2021. "Equilibrium analyses and operational designs of a coupled market with substitutive and complementary ride-sourcing services to public transits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
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