IDEAS home Printed from https://ideas.repec.org/a/spr/cejnor/v29y2021i2d10.1007_s10100-020-00684-8.html
   My bibliography  Save this article

The effect of attacks on the railway network of Hungary

Author

Listed:
  • B. G. Tóth

    (National University of Public Service)

Abstract

Targeted attacks on the railway network of Hungary were modelled by using a weighted directed graph. Two attack strategies were analyzed, one based on the efficiency measure and one based on the betweenness centrality of the network elements. The results show that while the network elements with the most traffic make the efficiency to decrease the most, the network elements that make the efficiency to decrease the most are not always the busiest ones. The first network element to be destructed is always the Southern railway bridge (or its adjacent stations) at Budapest. The three Danube bridges become unusable in at most five steps. The next most endangered regions of the country to lose their railway connection to the rest of the network are the branch lines at Miskolc, and the three northeastern counties. As the national railway network is vital for the Hungarian Army, not only the protection of the highly threatened network elements is important but also the ability for their substitution which is mostly impossible due to the low ratio of electrified lines which implies the need for a larger fleet of diesel locomotives.

Suggested Citation

  • B. G. Tóth, 2021. "The effect of attacks on the railway network of Hungary," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 567-587, June.
    • Handle: RePEc:spr:cejnor:v:29:y:2021:i:2:d:10.1007_s10100-020-00684-8
    DOI: 10.1007/s10100-020-00684-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10100-020-00684-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10100-020-00684-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 581-603, December.
    2. Derrible, Sybil & Kennedy, Christopher, 2010. "The complexity and robustness of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3678-3691.
    3. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2004. "Error and attack tolerance of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 388-394.
    4. Jonas Johansson & Henrik Hassel & Alexander Cedergren, 2011. "Vulnerability analysis of interdependent critical infrastructures: case study of the Swedish railway system," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 7(4), pages 289-316.
    5. Renato Redondi & Paolo Malighetti & Stefano Paleari, 2011. "New Routes and Airport Connectivity," Networks and Spatial Economics, Springer, vol. 11(4), pages 713-725, December.
    6. Sybil Derrible & Christopher Kennedy, 2011. "Applications of Graph Theory and Network Science to Transit Network Design," Transport Reviews, Taylor & Francis Journals, vol. 31(4), pages 495-519.
    7. Johanna Ludvigsen & Ronny Klæboe, 2014. "Extreme weather impacts on freight railways in Europe," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(1), pages 767-787, January.
    8. Glover, Donald R & Simon, Julian L, 1975. "The Effect of Population Density on Infrastructure: The Case of Road Building," Economic Development and Cultural Change, University of Chicago Press, vol. 23(3), pages 453-468, April.
    9. Voltes-Dorta, Augusto & Rodríguez-Déniz, Héctor & Suau-Sanchez, Pere, 2017. "Vulnerability of the European air transport network to major airport closures from the perspective of passenger delays: Ranking the most critical airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 119-145.
    10. Zhu, Weihua & Liu, Kai & Wang, Ming & Yan, Xiaoyong, 2018. "Enhancing robustness of metro networks using strategic defense," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1081-1091.
    11. Zhang, Pengcheng & Peeta, Srinivas, 2011. "A generalized modeling framework to analyze interdependencies among infrastructure systems," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 553-579, March.
    12. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    13. G. Paul & T. Tanizawa & S. Havlin & H. Stanley, 2004. "Optimization of robustness of complex networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 187-191, March.
    14. Yuxin He & Jin Qin & Jian Hong, 2017. "Comparative analysis of quantitative efficiency evaluation methods for transportation networks," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-14, April.
    15. Marchiori, Massimo & Latora, Vito, 2000. "Harmony in the small-world," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(3), pages 539-546.
    16. Cats, Oded, 2017. "Topological evolution of a metropolitan rail transport network: The case of Stockholm," Journal of Transport Geography, Elsevier, vol. 62(C), pages 172-183.
    17. Gedik, Ridvan & Medal, Hugh & Rainwater, Chase & Pohl, Ed A. & Mason, Scott J., 2014. "Vulnerability assessment and re-routing of freight trains under disruptions: A coal supply chain network application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 45-57.
    18. Bono, Flavio & Gutiérrez, Eugenio, 2011. "A network-based analysis of the impact of structural damage on urban accessibility following a disaster: the case of the seismically damaged Port Au Prince and Carrefour urban road networks," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1443-1455.
    19. Jingyi Lin & Yifang Ban, 2013. "Complex Network Topology of Transportation Systems," Transport Reviews, Taylor & Francis Journals, vol. 33(6), pages 658-685, November.
    20. Fikar, Christian & Hirsch, Patrick & Posset, Martin & Gronalt, Manfred, 2016. "Impact of transalpine rail network disruptions: A study of the Brenner Pass," Journal of Transport Geography, Elsevier, vol. 54(C), pages 122-131.
    21. Dawson, David & Shaw, Jon & Roland Gehrels, W., 2016. "Sea-level rise impacts on transport infrastructure: The notorious case of the coastal railway line at Dawlish, England," Journal of Transport Geography, Elsevier, vol. 51(C), pages 97-109.
    22. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2003. "Efficiency of scale-free networks: error and attack tolerance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 622-642.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luo, Ding & Cats, Oded & van Lint, Hans & Currie, Graham, 2019. "Integrating network science and public transport accessibility analysis for comparative assessment," Journal of Transport Geography, Elsevier, vol. 80(C).
    2. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    3. Rodríguez-Núñez, Eduardo & García-Palomares, Juan Carlos, 2014. "Measuring the vulnerability of public transport networks," Journal of Transport Geography, Elsevier, vol. 35(C), pages 50-63.
    4. Kashin Sugishita & Yasuo Asakura, 2021. "Vulnerability studies in the fields of transportation and complex networks: a citation network analysis," Public Transport, Springer, vol. 13(1), pages 1-34, March.
    5. Jin Qin & Yuxin He & Linglin Ni, 2014. "Quantitative Efficiency Evaluation Method for Transportation Networks," Sustainability, MDPI, vol. 6(12), pages 1-15, November.
    6. Cats, Oded & Krishnakumari, Panchamy, 2020. "Metropolitan rail network robustness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    7. Khademi, Navid & Babaei, Mohsen & Schmöcker, Jan-Dirk & Fani, Amirhossein, 2018. "Analysis of incident costs in a vulnerable sparse rail network – Description and Iran case study," Research in Transportation Economics, Elsevier, vol. 70(C), pages 9-27.
    8. Woodburn, Allan, 2019. "Rail network resilience and operational responsiveness during unplanned disruption: A rail freight case study," Journal of Transport Geography, Elsevier, vol. 77(C), pages 59-69.
    9. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    10. Zhang, Jianhua & Song, Bo & Zhang, Zhaojun & Liu, Haikuan, 2014. "An approach for modeling vulnerability of the network of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 127-136.
    11. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    12. Rui Ding & Norsidah Ujang & Hussain Bin Hamid & Mohd Shahrudin Abd Manan & Rong Li & Safwan Subhi Mousa Albadareen & Ashkan Nochian & Jianjun Wu, 2019. "Application of Complex Networks Theory in Urban Traffic Network Researches," Networks and Spatial Economics, Springer, vol. 19(4), pages 1281-1317, December.
    13. Chan, Ho-Yin & Chen, Anthony & Li, Guoyuan & Xu, Xiangdong & Lam, William, 2021. "Evaluating the value of new metro lines using route diversity measures: The case of Hong Kong's Mass Transit Railway system," Journal of Transport Geography, Elsevier, vol. 91(C).
    14. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    15. Kermanshah, A. & Derrible, S., 2016. "A geographical and multi-criteria vulnerability assessment of transportation networks against extreme earthquakes," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 39-49.
    16. Mostafa Bababeik & Mohammad Mahdi Nasiri & Navid Khademi & Anthony Chen, 2019. "Vulnerability evaluation of freight railway networks using a heuristic routing and scheduling optimization model," Transportation, Springer, vol. 46(4), pages 1143-1170, August.
    17. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.
    18. Jing, Weiwei & Xu, Xiangdong & Pu, Yichao, 2020. "Route redundancy-based approach to identify the critical stations in metro networks: A mean-excess probability measure," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    19. Liu, Qing & Yang, Yang & Ng, Adolf K.Y. & Jiang, Changmin, 2023. "An analysis on the resilience of the European port network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    20. Lu, Qing-Chang, 2018. "Modeling network resilience of rail transit under operational incidents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 227-237.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:cejnor:v:29:y:2021:i:2:d:10.1007_s10100-020-00684-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.