Abstract
We develop practical OR models to support decision making in the design and management of public car-sharing or bicycle-sharing systems. We develop a network flow model with proportionality constraints to estimate the flow of bicycles within the network, and to estimate the number of trips supported by the system given an initial allocation of bicycles at each station. Furthermore, the number of docks needed at each station, to support the flow, can also be estimated. We also examine the impact of periodic redistribution of bicycles in the network to support more flows, and the location choices of bicycle stations. We conduct our numerical analysis using transit data from the train and bus operators in Singapore. Given that a substantial proportion of the passengers in the train system commute short distance – more than 16% of the passengers alight within 2 stops from the start station – this forms a latent segment of demand for the bicycle-sharing program. We argue that for the bicycle-sharing system to be most effective for this customer segment, the system must deploy the right number of bicycles at the right place, as this affects the utilization rate of the bicycles, how the bicycles circulate within the system, and also the effectiveness of any redistribution strategy. The same approach can be extended to incorporate the issue of station location choices, by incorporating the proportional flow constraints into the MIP formulation. Using a set of bus transit data, we implemented this approach to identify the ideal locations for the bicycle stations in a new town in Singapore, to support the movement of passengers from residential areas to the train station.
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Notes
- 1.
Note that we have assumed all passengers will use bicycles to substitute their short distance MRT trips (within 2-Stop), upon the availability of the bicycles. We have thus actually obtained a gross over-estimate on the total volume of trips that can be substituted by bicycles. In reality, only a small percentage of the short distance passengers captured in the data will choose to use bicycles, say 10%. Therefore, all our numbers must be scaled down by a factor of 10 accordingly. In this case, we can see that for α = 40, the maximum number of bicycle docks we need to setup among all stations is no more than 80 for our system.
- 2.
If we assume that the take-up rate for bicycle trip is only 10% of the full demand, then the corresponding number of docks needed will be reduced by 90%, i.e., from 700 to 70 docks.
- 3.
Housing and Development Board – a statutory board of the Singapore Government responsible for public housing.
- 4.
We thank Prof Gideon Weiss for pointing this out.
References
Angeloudis P, Hu J, Bell MG (2014) A strategic repositioning algorithm for bicycle-sharing schemes. Transportmetrica A 10(8):759–774
Benchimol M, Benchimol P, Chappert B, De La Taille A, Laroche F, Meunier F, Robinet L (2011) Balancing the stations of a self service “bike hire” system. RAIRO-Oper Res 45(1):37–61
DeMaio P (2009) Bicycle-sharing: history, impacts, models of provision, and future. J Public Transp 12(4):41–56
Dector-Vega G, Snead C, Phillips A (2008) Feasibility study for a central london cycle hire scheme. Technical report, Transport for London
Forbes (2017). https://www.forbes.com/sites/ywang/2017/06/20/worth-1-billion-but-whats-really-driving-chinas-bike-sharingboom/#608d7e69427e
Ghosh S, Varakantham P, Adulyasak Y, Jaillet P (2017) Dynamic repositioning to reduce lost demand in bike sharing systems. J Artif Intell Res 58:387–430
Kloimüllner C, Raidl GR (2017) Full-load route planning for balancing bike shaing systems by logic-based Benders decomposition. Networks 69(3):270–289
Li Y, Szeto WY, Long J, Shui CS (2016) A multiple type bike repositioning problem. Transp Res Part B Methodol 90:263–278
MetroBike LLC (2011) The bike sharing blog. http://bike-sharing.blogspot.com/. Accessed 1 Oct 2011
MetroBike LLC (2012) Have card, will travel. http://bike-sharing.blogspot.com/. Accessed 17 Jan 2012
MetroBike LLC (2017) The bike sharing blog. http://bike-sharing.blogspot.com/. Accessed 19 Aug 2017
Natarajan K, Song M, Teo CP (2009) Persistency model and its applications in choice modeling. Manag Sci 55(3):453–469
Natarajan K, Teo CP, Zheng Z (2011) Mixed zero-one linear programs under objective uncertainty: a completely positive representation. Oper Res 59(3):713–728
Raviv T, Tzur M, Forma IA (2013) Static repositioning in a bike-sharing system: models and solution approaches. EURO J Transp Logist 2(3):187–229
Russell M, DeMaio P (2017) The bike sharing world map. http://bike-sharing.blogspot.com/
Schuijbroek J, Hampshire RC, van Hoeve WJ (2017) Inventory rebalancing and vehicle routing in bike sharing systems. Eur J Oper Res 257(3):992–1004
Serna A, Gerrikagoitia JK, Bernabe U, Ruiz T (2017) A method to assess sustainable mobility for sustainable tourism: the case of the public bike systems. In: Information and communication technologies in tourism 2017. Springer, Cham, pp 727–739
Shu J, Chou MC, Liu Q, Teo CP, Wang IL (2013) Models for effective deployment and redistribution of bicycles within public bicycle-sharing systems. Oper Res 61(6):1346–1359
The Economist (2011) Why a Boris bike can be an existential hell. http://www.economist.com/blogs/gulliver/2011/04/londonscycle-hirescheme/
Acknowledgements
We thank Singapore Mass Rapid Transit and Land Transport Authority for providing the data used in this research. This research was supported in part by NUS Academic Research Fund R-314-000-078-112.
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Chou, M.C., Liu, Q., Teo, CP., Yeo, D. (2019). Models for Effective Deployment and Redistribution of Shared Bicycles with Location Choices. In: Hu, M. (eds) Sharing Economy. Springer Series in Supply Chain Management, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-030-01863-4_17
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