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The controllability of China’s high-speed rail network in terms of delivering emergency supplies

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  • Liu, Jie
  • Schonfeld, Paul M.
  • Shuai, Chunyan
  • He, Mingwei
  • Wang, Kelvin C.P.

Abstract

Network control theory is first applied here to study the controllability of a High-speed Rail Network (HRN) in terms of delivering emergency supplies. The full controllability or target controllability of an HRN (i.e., controlling the amount of emergency supplies delivered at all stations or target control stations) can be achieved when the amount of emergency supplies transported from some appropriate stations is efficiently controlled. To identify the optimized controlling stations, a model is proposed for minimizing the number of controlling stations and maximizing the sum of trains departing from controlling stations, which effectively and quickly controls an HRN in terms of delivering emergency supplies. The proposed model is demonstrated in a case in which the delivery of emergency supplies by China’s HRN is controlled during the COVID-19 epidemic. The result shows that the sum of trains departing from the optimized controlling stations obtained through the proposed method is higher than that of the optimized controlling stations obtained through the commonly used maximum match method, and thus, the proposed method can obtain a better solution. The proposed method helps operators to identify the optimized controlling stations for effectively controlling an HRN in terms of delivering emergency supplies, and thus helping respond to emergency events.

Suggested Citation

  • Liu, Jie & Schonfeld, Paul M. & Shuai, Chunyan & He, Mingwei & Wang, Kelvin C.P., 2022. "The controllability of China’s high-speed rail network in terms of delivering emergency supplies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    • Handle: RePEc:eee:phsmap:v:606:y:2022:i:c:s0378437122006586
    DOI: 10.1016/j.physa.2022.128055
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    References listed on IDEAS

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    1. Xuelei Meng & Wanli Xiang & Li Wang, 2015. "Controllability of Train Service Network," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-8, May.
    2. Yu, Xiaoyao & Liang, Yongqing & Wang, Xiaomeng & Jia, Tao, 2021. "The network asymmetry caused by the degree correlation and its effect on the bimodality in control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    3. Yang-Yu Liu & Jean-Jacques Slotine & Albert-László Barabási, 2011. "Controllability of complex networks," Nature, Nature, vol. 473(7346), pages 167-173, May.
    4. Ruiz, Ruben & Stutzle, Thomas, 2007. "A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2033-2049, March.
    5. Jianxi Gao & Yang-Yu Liu & Raissa M. D'Souza & Albert-László Barabási, 2014. "Target control of complex networks," Nature Communications, Nature, vol. 5(1), pages 1-8, December.
    6. J.H. Ruan & X.P. Wang & F.T.S. Chan & Y. Shi, 2016. "Optimizing the intermodal transportation of emergency medical supplies using balanced fuzzy clustering," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4368-4386, July.
    7. Lu Zeng & Jun Liu & Yong Qin & Li Wang & Jie Yang, 2018. "A Passenger Flow Control Method for Subway Network Based on Network Controllability," Discrete Dynamics in Nature and Society, Hindawi, vol. 2018, pages 1-12, September.
    8. Chen, Shi-Ming & Xu, Yun-Fei & Nie, Sen, 2017. "Robustness of network controllability in cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 536-539.
    9. Rinaldi, Marco, 2018. "Controllability of transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 381-406.
    Full references (including those not matched with items on IDEAS)

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