IDEAS home Printed from https://ideas.repec.org/a/taf/rjusxx/v20y2016isup1p38-49.html
   My bibliography  Save this article

Evaluation of the resilience of air transportation network with adaptive capacity

Author

Listed:
  • Suhyung Yoo
  • Hwasoo Yeo

Abstract

Securing network resilience of air transportation system is essential to provide a stable level of service as one of major transport modes carrying international passengers and freights. In 2014, about 851 million passengers and 39 billion pounds of freights were delivered by over 9.5 million flights in the United States. As seen in Iceland volcano eruption in 2010, a deficiency of hub airports can bring a huge impact on the whole transport system and even on the world economy. So how the failure of individual node affects the overall network resilience is an important issue to study. Air transportation is known to be a scale-free network, which has few of hubs having high degree. So it is relatively robust against failure but vulnerable to targeted attack on a hub. There are numerous studies devoted to measure node vulnerability and evaluate network robustness; however, previous studies could not consider the node capacity for evaluating overall network performance. This study focuses on the network resilience, where the nodes are located in a real space and have a capacity to function. Using the data from Federal Aviation Administration, the simulation demonstrates and evaluates the resilience of the US air transportation network. This study proposes the indices of adaptative capacity for quantifying network resilience, which represent the ability of a network to replace an attacked node by other adjacent nodes. The simulation has two parts to measure the adaptive capacity of networks: under a single attack and a sustained attack. The results identify the susceptible nodes degrading the adaptive capacity of the network and evaluate each sub-network’s resilience in case of cascading node failures. Therefore, this study can help us to diagnose the vulnerable node and contribute the plan for improvement of network resilience.

Suggested Citation

  • Suhyung Yoo & Hwasoo Yeo, 2016. "Evaluation of the resilience of air transportation network with adaptive capacity," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 20(sup1), pages 38-49, July.
  • Handle: RePEc:taf:rjusxx:v:20:y:2016:i:sup1:p:38-49
    DOI: 10.1080/12265934.2016.1166979
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/12265934.2016.1166979
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/12265934.2016.1166979?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. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    2. M. T. Gastner & M. E.J. Newman, 2006. "The spatial structure of networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 49(2), pages 247-252, January.
    3. O. Woolley-Meza & C. Thiemann & D. Grady & J. Lee & H. Seebens & B. Blasius & D. Brockmann, 2011. "Complexity in human transportation networks: a comparative analysis of worldwide air transportation and global cargo-ship movements," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 84(4), pages 589-600, December.
    4. Sullivan, J.L. & Novak, D.C. & Aultman-Hall, L. & Scott, D.M., 2010. "Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 323-336, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Meisam Akbarzadeh & Soroush Memarmontazerin & Sybil Derrible & Sayed Farzin Salehi Reihani, 2019. "The role of travel demand and network centrality on the connectivity and resilience of an urban street system," Transportation, Springer, vol. 46(4), pages 1127-1141, August.
    2. Bai, Xiwen & Ma, Zhongjun & Zhou, Yaoming, 2023. "Data-driven static and dynamic resilience assessment of the global liner shipping network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    3. Xu, Zizhen & Chopra, Shauhrat S., 2022. "Network-based Assessment of Metro Infrastructure with a Spatial–temporal Resilience Cycle Framework," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    4. Jakšić, Zoran & Janić, Milan, 2020. "Modeling resilience of the ATC (Air Traffic Control) sectors," Journal of Air Transport Management, Elsevier, vol. 89(C).
    5. Xiaoqian Sun & Sebastian Wandelt, 2021. "Robustness of Air Transportation as Complex Networks:Systematic Review of 15 Years of Research and Outlook into the Future," Sustainability, MDPI, vol. 13(11), pages 1-19, June.
    6. Jiangang Shi & Shiping Wen & Xianbo Zhao & Guangdong Wu, 2019. "Sustainable Development of Urban Rail Transit Networks: A Vulnerability Perspective," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    7. Wang, Xinglong & Peng, Jinhan & Tang, Junqing & Lu, Qiuchen & Li, Xiaowei, 2022. "Investigating the impact of adding new airline routes on air transportation resilience in China," Transport Policy, Elsevier, vol. 125(C), pages 79-95.

    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. Hu, Xinlei & Huang, Jie & Shi, Feng, 2022. "A robustness assessment with passenger flow data of high-speed rail network in China," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    2. Xia, Yongxiang & Liu, Nianjun & Iu, Herbert H.C., 2009. "Oscillation and chaos in a deterministic traffic network," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1700-1704.
    3. 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.
    4. Guo, Shengmin & Wu, Ruoqian & Tong, Qingfeng & Zeng, Guanwen & Yang, Jian & Chen, Long & Zhu, Tongyu & Lv, Weifeng & Li, Daqing, 2018. "Is city traffic damaged by torrential rain?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1073-1080.
    5. Ikeda, Nobutoshi, 2010. "Impact of initial lattice structures on networks generated by traces of random walks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3336-3347.
    6. Sean Wilkinson & Sarah Dunn & Shu Ma, 2012. "The vulnerability of the European air traffic network to spatial hazards," 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. 60(3), pages 1027-1036, February.
    7. Nazli Yonca Aydin & H. Sebnem Duzgun & Friedemann Wenzel & Hans Rudolf Heinimann, 2018. "Integration of stress testing with graph theory to assess the resilience of urban road networks under seismic hazards," 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. 91(1), pages 37-68, March.
    8. 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.
    9. Dunn, Sarah & Wilkinson, Sean, 2017. "Hazard tolerance of spatially distributed complex networks," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 1-12.
    10. Braha, Dan & Stacey, Blake & Bar-Yam, Yaneer, 2011. "Corporate competition: A self-organized network," MPRA Paper 32142, University Library of Munich, Germany.
    11. Richard Connors & David Watling, 2015. "Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation," Networks and Spatial Economics, Springer, vol. 15(2), pages 367-395, June.
    12. Sanjeev Goyal & Fernando Vega-Redondo, 2000. "Learning, Network Formation and Coordination," Econometric Society World Congress 2000 Contributed Papers 0113, Econometric Society.
    13. Quayle, A.P. & Siddiqui, A.S. & Jones, S.J.M., 2006. "Preferential network perturbation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 823-840.
    14. Chen, Lei & Yue, Dong & Dou, Chunxia, 2019. "Optimization on vulnerability analysis and redundancy protection in interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1216-1226.
    15. Xiao‐Bing Hu & Hang Li & XiaoMei Guo & Pieter H. A. J. M. van Gelder & Peijun Shi, 2019. "Spatial Vulnerability of Network Systems under Spatially Local Hazards," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 162-179, January.
    16. Bálint Mészáros & István Simon & Zsuzsanna Dosztányi, 2009. "Prediction of Protein Binding Regions in Disordered Proteins," PLOS Computational Biology, Public Library of Science, vol. 5(5), pages 1-18, May.
    17. Irina Rish & Guillermo Cecchi & Benjamin Thyreau & Bertrand Thirion & Marion Plaze & Marie Laure Paillere-Martinot & Catherine Martelli & Jean-Luc Martinot & Jean-Baptiste Poline, 2013. "Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-15, January.
    18. Wang, Zhuoyang & Chen, Guo & Hill, David J. & Dong, Zhao Yang, 2016. "A power flow based model for the analysis of vulnerability in power networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 105-115.
    19. Bellingeri, Michele & Cassi, Davide & Vincenzi, Simone, 2014. "Efficiency of attack strategies on complex model and real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 174-180.
    20. Cats, Oded & Jenelius, Erik, 2015. "Planning for the unexpected: The value of reserve capacity for public transport network robustness," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 47-61.

    More about this item

    Statistics

    Access and download statistics

    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:taf:rjusxx:v:20:y:2016:i:sup1:p:38-49. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/rjus20 .

    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.