Pre-disaster Investment Model for Strengthening the Chinese Railway System Under Earthquakes

Chinese railway system serves as an important role for the economy of China and the travel needs of its citizens. As China is subject to frequent earthquake events, it is important to investigate how to strengthen the railway system to retain its service after earthquakes. This paper proposes a comprehensive methodology to suggest the optimal investment plan using historical earthquake events data and geographic information system (GIS) technology. The proposed optimization model minimizes the expected service loss under future earthquakes subject to an investment budget constraint. The expected service loss is constructed at the service layer of the Chinese railway system that is determined by the damage state of the railway link as well as the function restoration curve at the physical layer. Monte Carlo simulation and Genetic Algorithm are applied to solve the optimization model effectively. Numerical results show that the solution suggested by the proposed optimization model is more responsive to the earthquake impact on the railway system compared with plans suggested by topology-based methods. The proposed methodology can be extended to investigate the investment plans for other transportation systems under threats from natural disasters.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AR050 Standing Committee on Railroad Track Structure System Design.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Yan, Yongze
    • He, Xiaozheng
    • Hong, Liu
    • Ouyang, Min
    • Peeta, Srinivas
  • Conference:
  • Date: 2016

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; References; Tables;
  • Pagination: 18p
  • Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01592031
  • Record Type: Publication
  • Report/Paper Numbers: 16-2325
  • Files: PRP, TRIS, TRB, ATRI
  • Created Date: Feb 29 2016 4:54PM