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Pricing in vehicle sharing systems: optimization in queuing networks with product forms

Author

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  • Ariel Waserhole

    (Grenoble-INP/UJF-Grenoble 1/CNRS, G-SCOP UMR5272
    LIX CNRS, École Polytechnique)

  • Vincent Jost

    (Grenoble-INP/UJF-Grenoble 1/CNRS, G-SCOP UMR5272
    LIX CNRS, École Polytechnique)

Abstract

One-way vehicle sharing systems (VSS) such as Vélib’ Paris are flourishing. The usefulness of VSS for users is highly impacted by the availability of vehicles and parking spots. Most existing systems are ruled by the trips of users. We study the potential interest of influencing the users to improve the performance of the system. We assume that each user is associated with a pair origin–destination (O–D) of stations, and only interacts with the system if his O–D trip is available. We consider leverage that can influence the rate of user requests for each pair O–D, such as a price that will be prohibitive for a prescribed proportion of users. We focus on optimizing the number of trips taken in the system. To provide exact formulas and analytical insights, transportation times are assumed to be null, stations to have infinite capacities and the demand to be stationary over time. In other words, VSS are modelled as closed queuing networks with infinite buffer capacity and Markovian demands. We propose a heuristic based on computing a Maximum Circulation on the demand graph together with a convex integer program solved optimally by a greedy algorithm. For $$M$$ M stations and $$N$$ N vehicles, the performance ratio of this heuristic is proved to be exactly $$N/(N+M-1)$$ N / ( N + M - 1 ) . We discuss our understanding on the possibility of extending this result to more realistic models in the perspectives. The complexity of computing optimum policies remains open. Insights on this issue are provided in the Appendix. The Appendix also contains an example showing that VSS can have poor performances without regulation.

Suggested Citation

  • Ariel Waserhole & Vincent Jost, 2016. "Pricing in vehicle sharing systems: optimization in queuing networks with product forms," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 5(3), pages 293-320, August.
  • Handle: RePEc:spr:eurjtl:v:5:y:2016:i:3:d:10.1007_s13676-014-0054-4
    DOI: 10.1007/s13676-014-0054-4
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    References listed on IDEAS

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    1. Lin, Jenn-Rong & Yang, Ta-Hui, 2011. "Strategic design of public bicycle sharing systems with service level constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(2), pages 284-294, March.
    2. repec:ucp:bkecon:9781884829987 is not listed on IDEAS
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    2. Liangpeng Gao & Yanjie Ji & Xingchen Yan & Yao Fan & Weihong Guo, 2021. "Incentive measures to avoid the illegal parking of dockless shared bikes: the relationships among incentive forms, intensity and policy compliance," Transportation, Springer, vol. 48(2), pages 1033-1060, April.
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    6. Sayarshad, Hamid R. & Chow, Joseph Y.J., 2017. "Non-myopic relocation of idle mobility-on-demand vehicles as a dynamic location-allocation-queueing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 60-77.
    7. Li, Shukai & Luo, Qi & Hampshire, Robert Cornelius, 2021. "Optimizing large on-demand transportation systems through stochastic conic programming," European Journal of Operational Research, Elsevier, vol. 295(2), pages 427-442.
    8. Saif Benjaafar & Shining Wu & Hanlin Liu & Einar Bjarki Gunnarsson, 2022. "Dimensioning On-Demand Vehicle Sharing Systems," Management Science, INFORMS, vol. 68(2), pages 1218-1232, February.
    9. Zhang, Si & Sun, Huijun & Wang, Xu & Lv, Ying & Wu, Jianjun, 2022. "Optimization of personalized price discounting scheme for one-way station-based carsharing systems," European Journal of Operational Research, Elsevier, vol. 303(1), pages 220-238.
    10. Hara, Yusuke & Hato, Eiji, 2018. "A car sharing auction with temporal-spatial OD connection conditions," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 723-739.
    11. Sharon Datner & Tal Raviv & Michal Tzur & Daniel Chemla, 2019. "Setting Inventory Levels in a Bike Sharing Network," Service Science, INFORMS, vol. 53(1), pages 62-76, February.
    12. Zhao, Chunkai & Wang, Yuhang & Ge, Zhenyu, 2023. "Is digital finance environmentally friendly in China? Evidence from shared-bike trips," Transport Policy, Elsevier, vol. 138(C), pages 129-143.
    13. Anton Braverman & J. G. Dai & Xin Liu & Lei Ying, 2019. "Empty-Car Routing in Ridesharing Systems," Operations Research, INFORMS, vol. 67(5), pages 1437-1452, September.
    14. Repoux, Martin & Kaspi, Mor & Boyacı, Burak & Geroliminis, Nikolas, 2019. "Dynamic prediction-based relocation policies in one-way station-based carsharing systems with complete journey reservations," Transportation Research Part B: Methodological, Elsevier, vol. 130(C), pages 82-104.
    15. Richter, Magnus & Souren, Rainer, 2018. "If sharing is everything, then it is nothing: A multidisciplinary survey on basic terms, views and current research topics," Ilmenauer Schriften zur Betriebswirtschaftslehre, Technische Universität Ilmenau, Institut für Betriebswirtschaftslehre, volume 2, number 22018.
    16. 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.
    17. Liu, Yang & Xie, Jiaohong & Chen, Nan, 2022. "Stochastic one-way carsharing systems with dynamic relocation incentives through preference learning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).

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