Route Selection Optimization of Railway Passenger Station Based on Ant Colony Algorithm

In the railway station operation, route arrangement directly influence the operation efficiency of arrival and departure of trains, as well as the carrying capacity of station. As it is a large-scale combinatorial optimization problem with two-dimensional performance on both space and time, traditional algorithms can not satisfy the real- time request of station production due to the long time-consuming. In view of the characteristic of this question, the optimization model on route selection of passenger station is established in this paper, and the optimization algorithm of route selection based on the minimum maximum ant system is proposed. The technical problems of the algorithm, such as structural map of solution, pheromone model, heuristic information model, local search method and so on are discussed.

• Record URL:
  https://doi.org/10.1061/41039(345)50
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784410394
• Supplemental Notes:
  • © 2009 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Lu, Hongxia
  • Ni, Shaoquan
  • Chen, Tao
• Conference:
  • Second International Conference on Transportation Engineering
  • Location: Chengdu , China
  • Date: 2009-7-25 to 2009-7-27
• Publication Date: 2009-7

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 297-302
• Monograph Title: International Conference on Transportation Engineering 2009

Subject/Index Terms

• TRT Terms: Algorithms; Optimization; Passenger trains; Railroad stations; Routes and routing; Station operations
• Subject Areas: Operations and Traffic Management; Passenger Transportation; Planning and Forecasting; Railroads; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01534539
• Record Type: Publication
• ISBN: 9780784410394
• Files: TRIS, ASCE
• Created Date: Aug 14 2014 9:19AM