Abstract
With respect to the maximum revenue for the inter-city railway passenger transportation channel system with different grades of parallel trains, this paper has studied the matching relations between the system revenue and the passenger flow demand under confirmed demand conditions, analyzed the behavior selection process of passengers for trains with different speed grades within the channel, confirmed the passenger train flow transformation equation based on Logit sharing rate model as well as the collaborative optimization of stop stations and graded ticket fares, established the maximum revenue model of the system, and designed the hybrid particle swarm harmony search algorithm to solve the model. Besides, the new solution comparative law for the algorithm has also been formulated, which can improve the occurring probability of excellent solutions. Finally, verification has been made by taking Zhengzhou-Xi’an Railway Passenger Transportation Channel as an example, which has showed the effectiveness of the model and the algorithm, and the research results have showed that the redistribution of passenger flow realized through the stop stations and graded ticket fare policy can better improve the maximum revenue of the system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Shan, X. H. 2012. Study on railway revenue management model and its application in passenger transportation, 20–29. Beijing: China Academy of Railway Sciences.
Shi, F., G. H. Zheng, and Q. Gu. 2002. Optimal dynamic pricing of railway passenger ticket. Journal of the China Railway Society 24 (1): 1–4.
Bao, Y. 2013. The theory and methods for railway seat inventory control, 113–128. Beijing: Beijing Jiaotong University.
Nuzzolo, Agostino, Umberto Crisalli, and Francesca Gangemi. 2000. A behavioural choice model for the evaluation of railway supply and pricing policies. Transportation Research Part A: Policy and Practice 34 (5): 395–404.
Wu, W. X. 2011. Research on the share rate of passenger flow and transportation organization strategy in railway transportation corridor. China Railway Science 32 (2): 126–129.
Mi, Jie. 2006. MLE of parameters of location-scale distribution for complete and partially grouped data. Journal of Statistical Planning and Inference 136: 3565–3582.
Mahdavi, M., M. Fesanghary, E. Damangir. 2007. An improved harmony search algorithm for solving optimization problems. Applied Mathematics and Computation 188 (2): 1567–1579.
Peng, H. Q., and Y. J. Zhu. 2012. Intercity train operation schemes based on passenger flow dynamic assignment. Journal of Transportation Systems Engineering and Information Technology 47 (3): 484–489.
Acknowledgments
Fund: National Social Science Fund (14XGL011). The Natural Science Fund of Gansu Province (1506RJZA062)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media Singapore
About this paper
Cite this paper
Chen, X., Zhao, X. (2018). Revenue Model for the Inter-City Railway System Based on the Stop Stations and Graded Ticket Fares. In: Wang, W., Bengler, K., Jiang, X. (eds) Green Intelligent Transportation Systems. GITSS 2016. Lecture Notes in Electrical Engineering, vol 419. Springer, Singapore. https://doi.org/10.1007/978-981-10-3551-7_9
Download citation
DOI: https://doi.org/10.1007/978-981-10-3551-7_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3550-0
Online ISBN: 978-981-10-3551-7
eBook Packages: EngineeringEngineering (R0)