An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand

The development of high-speed railways (HSR) in China has attracted a large number of passengers from highway and aviation to railways due to their comfort and high speed. In this case, HSR passenger transportation can improve the operating income by optimizing the ticket allocation. Here, the authors propose an optimization method of multiclass price railway passenger transport ticket allocation under high passenger demand. First, for the “censored data” problem in the railway passenger demand forecast, the authors constructed an unconstrained model of railway passenger demand and solved the unconstrained demand through an expectation-maximization algorithm. Then, on this basis, the authors use gray neural networks (GNNs) to predict the passenger demand of different origins and destinations (ODs), and according to the prediction results, the authors propose two ticket allocation methods based on operation and capacity control: accurate predivided model and fuzzy predivided model. And the authors solve this problem by constructing a particle swarm optimization algorithm. Lastly, the authors use examples to prove that the proposed ticket allocation method can meet the passengers’ needs and have good economic benefits.

• Record URL:
  https://doi.org/10.1155/2020/8860115
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/5121625
• Supplemental Notes:
  • © 2020 Wang Bin et al.
• Authors:
  • Bin, Wang
  • Ni, Shaoquan
  • Jin, Fucai
  • Huang, Zixu
• Publication Date: 2020-9

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: Article ID 8860115
• Serial:
  • Journal of Advanced Transportation
  • Volume: 2020
  • Publisher: John Wiley & Sons, Incorporated
  • ISSN: 0197-6729
  • EISSN: 2042-3195
  • Serial URL: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2042-3195
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Algorithms; High speed rail; Methodology; Neural networks; Optimization; Passenger trains; Ticketing; Travel demand
• Geographic Terms: China
• Subject Areas: Passenger Transportation; Railroads;

Filing Info

• Accession Number: 01755148
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 21 2020 9:52AM