IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v189y2024ics019126152400136x.html

A topological network connectivity design problem based on spectral analysis

Author

Listed:
  • Nakayama, Shoichiro
  • Kobayashi, Shun-ichi
  • Yamaguchi, Hiromichi

Abstract

How to improve network connectivity and which parts of the network are vulnerable are critical issues. We begin by defining an equal distribution problem, in which supplies are distributed equally to all nodes in the network. We then derive a topological network connectivity measure from the convergence speed, which is the second minimum eigenvalue of a Laplacian network matrix. Based on the equal distribution problem, we propose a method for identifying critical links for network connectivity using the derivative of the second minimum eigenvalue. Furthermore, we develop a network design problem that maximizes topological connectivity within a budget creating strengthening network links. The problem is convex programming, and the solution is global. Furthermore, it can be converted into an identical semidefinite programming problem, which requires less computational effort. Finally, we test the developed problems on road networks in the Japanese prefectures of Ishikawa and Toyama to determine their applicability and validity.

Suggested Citation

  • Nakayama, Shoichiro & Kobayashi, Shun-ichi & Yamaguchi, Hiromichi, 2024. "A topological network connectivity design problem based on spectral analysis," Transportation Research Part B: Methodological, Elsevier, vol. 189(C).
  • Handle: RePEc:eee:transb:v:189:y:2024:i:c:s019126152400136x
    DOI: 10.1016/j.trb.2024.103012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S019126152400136X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.trb.2024.103012?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Hunt, Kyle & Zhuang, Jun, 2024. "A review of attacker-defender games: Current state and paths forward," European Journal of Operational Research, Elsevier, vol. 313(2), pages 401-417.
    2. Anthony Chen & Zhong Zhou & Piya Chootinan & Seungkyu Ryu & Chao Yang & S. Wong, 2011. "Transport Network Design Problem under Uncertainty: A Review and New Developments," Transport Reviews, Taylor & Francis Journals, vol. 31(6), pages 743-768.
    3. Fumitaka Kurauchi & Nobuhiro Uno & Agachai Sumalee & Yumiko Seto, 2009. "Network Evaluation Based on Connectivity Vulnerability," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 637-649, Springer.
    4. Bell, Michael G.H. & Kurauchi, Fumitaka & Perera, Supun & Wong, Walter, 2017. "Investigating transport network vulnerability by capacity weighted spectral analysis," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 251-266.
    5. Xu, Xiangdong & Chen, Anthony & Xu, Guangming & Yang, Chao & Lam, William H.K., 2021. "Enhancing network resilience by adding redundancy to road networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    6. J. Cole Smith & Churlzu Lim, 2008. "Algorithms for Network Interdiction and Fortification Games," Springer Optimization and Its Applications, in: Altannar Chinchuluun & Panos M. Pardalos & Athanasios Migdalas & Leonidas Pitsoulis (ed.), Pareto Optimality, Game Theory And Equilibria, pages 609-644, Springer.
    7. Cheung, Kam-Fung & Bell, Michael G.H. & Pan, Jing-Jing & Perera, Supun, 2020. "An eigenvector centrality analysis of world container shipping network connectivity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    8. Makoto Yamashita & Katsuki Fujisawa & Mituhiro Fukuda & Kazuhiro Kobayashi & Kazuhide Nakata & Maho Nakata, 2012. "Latest Developments in the SDPA Family for Solving Large-Scale SDPs," International Series in Operations Research & Management Science, in: Miguel F. Anjos & Jean B. Lasserre (ed.), Handbook on Semidefinite, Conic and Polynomial Optimization, chapter 0, pages 687-713, Springer.
    9. Akbarzadeh, Meisam & Salehi Reihani, Sayed Farzin & Samani, Keivan Aghababaei, 2019. "Detecting critical links of urban networks using cluster detection methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 288-298.
    10. Lo, Hong K. & Tung, Yeou-Koung, 2003. "Network with degradable links: capacity analysis and design," Transportation Research Part B: Methodological, Elsevier, vol. 37(4), pages 345-363, May.
    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. Yang, Junze & Xu, Xiangdong, 2026. "Identifying critical areas in urban road networks: A grid-based approach considering route redundancy," Reliability Engineering and System Safety, Elsevier, vol. 265(PA).
    2. Yang, Junze & Xu, Xiangdong & Ryu, Seungkyu, 2026. "Unveiling network vulnerability under multiple area-covering disruption scenarios: A scenario-enumeration-free model and empirical insights into targeted protection," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 206(C).
    3. Qu, Kai & Xu, Xiangdong & Zhou, Weiwen & Chen, Anthony, 2025. "Retrofit or new construction? Strategic budget allocation to improve transportation network redundancy under uncertain disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 198(C).
    4. Haritha, P.C. & Anjaneyulu, M.V.L.R., 2026. "A simple and efficient pre-selection method for partial network scan in critical link identification," Reliability Engineering and System Safety, Elsevier, vol. 265(PB).
    5. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    6. Barahimi, Amir Hossein & Eydi, Alireza & Aghaie, Abdolah, 2021. "Multi-modal urban transit network design considering reliability: multi-objective bi-level optimization," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    7. Tan, Zhijia & Yang, Hai & Tan, Wei & Li, Zhichun, 2016. "Pareto-improving transportation network design and ownership regimes," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 292-309.
    8. Ma, Wenxin & Liu, Zhiyong & Zheng, Chenhao & Baikejuli, Muladilijiang & Li, Ruimin, 2026. "Assessing and improving multi-perspective redundancy at segment level in multimodal transportation networks," Reliability Engineering and System Safety, Elsevier, vol. 265(PB).
    9. Sun, Chenshuo & Pei, Xin & Hao, Junheng & Wang, Yewen & Zhang, Zuo & Wong, S.C., 2018. "Role of road network features in the evaluation of incident impacts on urban traffic mobility," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 101-116.
    10. Sugiura, Satoshi & Chen, Anthony, 2021. "Vulnerability analysis of cut-capacity structure and OD demand using Gomory-Hu tree method," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 111-127.
    11. Zhaoqi Zang & Xiangdong Xu & Anthony Chen & Chao Yang, 2022. "Modeling the α-max capacity of transportation networks: a single-level mathematical programming formulation," Transportation, Springer, vol. 49(4), pages 1211-1243, August.
    12. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    13. Xu, Xiangdong & Chen, Anthony & Xu, Guangming & Yang, Chao & Lam, William H.K., 2021. "Enhancing network resilience by adding redundancy to road networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    14. Qu, Kai & Fan, Xiangyi & Xu, Xiangdong & Hanasusanto, Grani A. & Chen, Anthony, 2025. "Improving transportation network redundancy under uncertain disruptions via retrofitting critical components," Transportation Research Part B: Methodological, Elsevier, vol. 194(C).
    15. Faturechi, Reza & Miller-Hooks, Elise, 2014. "Travel time resilience of roadway networks under disaster," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 47-64.
    16. Balijepalli, Chandra & Oppong, Olivia, 2014. "Measuring vulnerability of road network considering the extent of serviceability of critical road links in urban areas," Journal of Transport Geography, Elsevier, vol. 39(C), pages 145-155.
    17. Shen, Siqian & Chen, Zhihao, 2013. "Optimization models for differentiating quality of service levels in probabilistic network capacity design problems," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 71-91.
    18. Hua Wang & Xiaoning Zhang, 2017. "Game theoretical transportation network design among multiple regions," Annals of Operations Research, Springer, vol. 249(1), pages 97-117, February.
    19. Gu, Yu & Chen, Anthony & Xu, Xiangdong, 2023. "Measurement and ranking of important link combinations in the analysis of transportation network vulnerability envelope buffers under multiple-link disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 118-144.
    20. Du, Muqing & Zhou, Jiankun & Chen, Anthony & Tan, Heqing, 2022. "Modeling the capacity of multimodal and intermodal urban transportation networks that incorporate emerging travel modes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:eee:transb:v:189:y:2024:i:c:s019126152400136x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    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.