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Building and Analyzing the Robustness of Interdependent Transportation Network for Hazmat Transporting Network and the Connected Traffic Network of Hazmat Transport

  • Peng Hu
  • Bin Shuai
  • Zhenyao Wu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 503)

Abstract

Hazardous Materials Transportation Network (HMTN) has very tight coupling with Traffic Flow Network of Hazmat Transportation (TFNHT). We build the interdependent system for the two networks. One of them is the HMTN of Zhangjiagang City, another is generated with power-law parameters which is considered as TFNHT. One node from the HMTN is random failed as initial emergency failure. It has an impact on one dependent node from the TFNHT. The dependent node would give traffic pressure on connected nodes from the HMTN. In order to know the stability and robustness of each single network, we propose the Node Failure Rate (NFR) to show the percentage of non-function with iterations going on. The two variables in simulation are different average degrees of the TFNHT and initial failure of one random selecting node which belongs to the set of different degrees. In terms of the basic data and the simulation results, we found that (1) the high average degree of the TFNHT has more impact on the interdependent network than the low average degree of it. It means that high values of average degree can lead interdependent weakness and instability; (2) We suggest that the node of low degree should be considered as the part of hazmat transportation routes, and it reduces as far as possible selecting the nodes of high degree when we design the HMTN for improving the robustness; (3) In the interdependent transportation network, the HMTN is more stability than the connected TFNHT and the two networks have the same NFR rising trend.

Notes

Acknowledgements

This paperwork is supported by the program which is National Natural Science Foundation of China and the Grant Number is 71173177. Another supporting program is MiaoZi project of Sichuan Province in China (Grant NO. 2014-013).

References

  1. 1.
    Buldyrev SV, Parshani R, Paul G, Stanley HE, Havlin S (2010) Catastrophic cascade of failures in interdependent networks. Nature 464(7291):1025–1028CrossRefGoogle Scholar
  2. 2.
    Vespignani A (2010) Complex networks: the fragility of interdependency. Nature 464(7291):984–985CrossRefGoogle Scholar
  3. 3.
    Gao J, Buldyrev SV, Stanley HE, Havlin S (2012) Networks formed from interdependent networks. Nat Phys 8(1):40–48CrossRefGoogle Scholar
  4. 4.
    Kenett DY, Gao J, Huang X, Shao S, Vodenska I, Buldyrev SV et al (2014) Network of interdependent networks: overview of theory and applications. In: Understanding Complex Systems, pp. 3–36Google Scholar
  5. 5.
    Veremyev A, Sorokin A, Boginski V, Pasiliao EL (2014) Minimum vertex cover problem for coupled interdependent networks with cascading failures. Eur J Oper Res 232(232):499–511MathSciNetCrossRefGoogle Scholar
  6. 6.
    Hines P, Balasubramaniam K, Sanchez EC (2009) Cascading failures in power grids. IEEE Potentials 28(5):24–30CrossRefGoogle Scholar
  7. 7.
    Zhai C, Zhang H, Xiao G, Pan TC (2017) Modeling and identification of worst-case cascading failures in power systemsGoogle Scholar
  8. 8.
    Gong J, Mitchell JE, Krishnamurthy A, Wallace WA (2014) An interdependent layered network model for a resilient supply chain. Omega 46(9):104–116CrossRefGoogle Scholar
  9. 9.
    Tang L, Jing K, He J, Stanley HE (2016) Complex interdependent supply chain networks: cascading failure and robustness. Physica A 443:58–69MathSciNetCrossRefGoogle Scholar
  10. 10.
    Kara BY, Verter V (2004) Designing a road network for hazardous materials transportation. Transp Sci 38(2):188–196CrossRefGoogle Scholar
  11. 11.
    Erkut E, Alp O (2007) Designing a road network for hazardous materials shipments. Comput Oper Res 34(5):1389–1405CrossRefGoogle Scholar
  12. 12.
    Erkut E, Gzara F (2008) Solving the hazmat transport network design problem. Comput Oper Res 35(7):2234–2247CrossRefGoogle Scholar
  13. 13.
    Chong PY, Shuai B, Deng SW, Yang J, Yin H (2015) Analysis on topological properties of Dalian hazardous materials road transportation network. Math Probl Eng 2015(1):1–11Google Scholar
  14. 14.
    Batagelj V, Mrvar A (2004) Pajek—analysis and visualization of large networks. In: Graph drawing software. Springer, Berlin, Heidelberg, pp. 77–103CrossRefGoogle Scholar
  15. 15.
    Pennock DM, Flake GW, Lawrence S, Glover EJ, Giles CL (2002) Winners don’t take all: Characterizing the competition for links on the web. Proc Natl Acad Sci USA 99(8):5207–5211CrossRefGoogle Scholar
  16. 16.
    Xia Q, Qian Y, Liu MF (2014) Route optimization for hazardous materials transportation based on environmental risk assessment—a case of Zhangjiagang. China Environ Sci 34(1):266–272Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Transportation and LogisticsSouthwest Jiaotong UniversityChengduChina

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