Warianty tytułu
Języki publikacji
Abstrakty
Purpose: The article aims to build a mathematical model of a bike-sharing station based on an appropriate queueing system and show the model's usefulness in practice. Design/methodology/approach: In designing the model, constructing a queueing system described by exponential distributions with a finite accumulating buffer was used. The existence of the steady state of the system and the global balance principle were used to obtain analytical results. Findings: The most important analytical results are the stationary probability distribution of the number of rented bikes, the so-called loss probability (the probability that the customer has to resign from sharing due to the lack of bikes), as well as the average (mean) values of the number of rented bikes. Originality/value: The paper fits into the broadly understood trend of research related to the smart city concept. The proposed model may be beneficial in practice when designing specific solutions related to the development of bicycle rental stations. (original abstract)
Słowa kluczowe
Rocznik
Strony
209--215
Opis fizyczny
Twórcy
autor
- Silesian University of Technology, Poland
autor
- Silesian University of Technology, Poland
Bibliografia
- 1. Adan, I., Resing, J. (2015). Queueing Systems. Eindhoven, available online: https://www.win.tue.nl/~iadan/queueing.pdf.
- 2. Ashqar, H.I., Elhenawy, M., Almannaa, M.H., Ghanem, A., Rakha, H.A., House, L. (2017). Modeling bike availability in a bike-sharing system using machine learning. 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), Naples, Italy, pp. 374-378.
- 3. Bose, S.K. (2002). An Introduction to Queueing Systems. New York: Springer Science+Business Media, LLC.
- 4. Chan, W.Ch. (2014). An Elementary Introduction to Queueing Systems. Singapore: World Scientific Publishing Co. Pte. Ltd.
- 5. Fishman, E. (2016). Bikeshare: A review of recent literature. Transport Reviews, vol. 36, iss. 1.
- 6. Heyman, D.P., Sobel, M.J. (1982). Stochastic Models in Operations Research. Vol. I: Stochastic Processes and Operating Characteristics. Mineola, New York: Dover Publications, Inc.
- 7. Lakatos, L., Szeidl, L., Telek, M. (2019). Introduction to Queueing Systems. In: Introduction to Queueing Systems with Telecommunication Applications. Cham: Springer.
- 8. Ng, Ch.-H., Soong, B.-H. (2008). Queueing Modelling Fundamentals with Applications in Communications Networks. Chichester: John Wiley & Sons, Inc.
- 9. Qian, X., Jaller, M., Circella, G. (2022). Equitable distribution of bikeshare stations: an optimization approach. Journal of Transport Geography, vol. 98, 103174.
- 10. Shortle, J.F., Thompson, J.M., Gross, D., Harris, C.M. (2018). Fundamentals of Queueing Theory. Hoboken: John Wiley & Sons, Inc.
- 11. Tijms, H.C. (2003). A First Course in Stochastic Models. Chichester: John Wiley & Sons, Inc.
- 12. Wang, X., Lindsey, G., Schoner, J.E., Harrison, A. (2015) Modeling bike share station activity: effects of nearby business and jobs on trips to and from stations. Journal of Urban Planning and Development, vol. 142, iss. 1, https://doi.org/10.1061/(ASCE)UP.1943- 5444.0000273.
- 13. Yang, H., Xie, K., Ozbay, K., Ma, Y., Wang, Z. (2018). Use of deep learning to predict daily usage of bike sharing systems. Transportation Research Record, vol. 2672, iss. 36, pp. 92-102.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171688988