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Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm

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  • Yunpeng Wang
  • Yuqin Feng
  • Wenxiang Li
  • William Case Fulcher
  • Li Zhang

Abstract

We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management.

Suggested Citation

  • Yunpeng Wang & Yuqin Feng & Wenxiang Li & William Case Fulcher & Li Zhang, 2014. "Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-9, June.
    • Handle: RePEc:hin:jnlmpe:356963
    DOI: 10.1155/2014/356963
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    Cited by:

    1. Ghavami, Seyed Morsal, 2019. "Multi-criteria spatial decision support system for identifying strategic roads in disaster situations," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 23-36.

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