Mean field analysis for inhomogeneous bike sharing systems

Christine Fricker; Nicolas Gast; Hanene Mohamed

doi:10.46298/dmtcs.3006

Christine Fricker ; Nicolas Gast ; Hanene Mohamed - Mean field analysis for inhomogeneous bike sharing systems

dmtcs:3006 - Discrete Mathematics & Theoretical Computer Science, January 1, 2012, DMTCS Proceedings vol. AQ, 23rd Intern. Meeting on Probabilistic, Combinatorial, and Asymptotic Methods for the Analysis of Algorithms (AofA'12) - https://doi.org/10.46298/dmtcs.3006

Mean field analysis for inhomogeneous bike sharing systemsArticle

Authors: Christine Fricker ¹; Nicolas Gast ^2,³; Hanene Mohamed ⁴

1 Networks, Algorithms and Probabilities
2 Middleware efficiently scalable
3 Ecole Polytechnique Fédérale de Lausanne
4 Modélisation aléatoire de Paris X [MODAL'X]

In the paper, bike sharing systems with stations having a finite capacity are studied as stochastic networks. The inhomogeneity is modeled by clusters. We use a mean field limit to compute the limiting stationary distribution of the number of bikes at the stations. This method is an alternative to analytical methods. It can be used even if a closed form expression for the stationary distribution is out of reach as illustrated on a variant. Both models are compared. A practical conclusion is that avoiding empty or full stations does not improve overall performance.

https://doi.org/10.46298/dmtcs.3006

Source: HAL:hal-01086055v1

Volume: DMTCS Proceedings vol. AQ, 23rd Intern. Meeting on Probabilistic, Combinatorial, and Asymptotic Methods for the Analysis of Algorithms (AofA'12)

Section: Proceedings

Published on: January 1, 2012

Imported on: January 31, 2017

Keywords: [INFO.INFO-PF] Computer Science [cs]/Performance [cs.PF],[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC],[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]

Licence: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

Bibliographic References

17 Documents citing this article

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