IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v636y2024ics0378437124000529.html
   My bibliography  Save this article

Random search processes on complex networks: From a static target to a moving object

Author

Listed:
  • Feng, Shiyuan
  • Weng, Tongfeng
  • Wang, Yan
  • Xu, Yubin
  • Ren, Zhuoming
  • Zhan, Li

Abstract

We investigate the transition behavior of search time from visiting a static target to hunting a moving one on complex networks. This is achieved by introducing a relative moving speed ratio that quantifies how the time scale of a searcher differs from that of a mobile target. We adopt mean first encounter time to quantify the search time required to capture a time-moving target and derive its analytical expression. Remarkably, we find that with the increase of their relative speed ratio, the expected search time increases gradually and finally approaches that of visiting a static target. This interesting transition behavior keeps invariant even changing the associated navigation strategies of the searcher and the moving object. These findings are confirmed by numerical results on various synthetic and real networks. Our work, for the first time, reveals the increasing pattern of search time from a static target to a moving one on networks.

Suggested Citation

  • Feng, Shiyuan & Weng, Tongfeng & Wang, Yan & Xu, Yubin & Ren, Zhuoming & Zhan, Li, 2024. "Random search processes on complex networks: From a static target to a moving object," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    • Handle: RePEc:eee:phsmap:v:636:y:2024:i:c:s0378437124000529
    DOI: 10.1016/j.physa.2024.129544
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124000529
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2024.129544?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. Wang, Yan & Cao, Xinxin & Weng, Tongfeng & Yang, Huijie & Gu, Changgui, 2021. "Lowest-degree preference random walks on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    2. Wang, Yan & Cao, Xinxin & Weng, Tongfeng & Yang, Huijie & Gu, Changgui, 2021. "A convex principle of search time for a multi-biased random walk on complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    3. Liu, Run-Ran & Jia, Chun-Xiao & Rong, Zhihai, 2019. "Effects of enhancement level on evolutionary public goods game with payoff aspirations," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 242-248.
    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. Wang, Mengyao & Pan, Qiuhui & He, Mingfeng, 2020. "The interplay of behaviors and attitudes in public goods game considering environmental investment," Applied Mathematics and Computation, Elsevier, vol. 382(C).
    2. Xu, Zhixiong & Xu, Zhehang & Zhang, Wei & Han, Xiao-Pu & Meng, Fanyuan, 2024. "Memory-based spatial evolutionary prisoner’s dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    3. Wang, Mie & Kang, HongWei & Shen, Yong & Sun, XingPing & Chen, QingYi, 2021. "The role of alliance cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    4. Song, Fanpeng & Wu, Jianliang & Fan, Suohai & Jing, Fei, 2020. "Transcendental behavior and disturbance behavior favor human development," Applied Mathematics and Computation, Elsevier, vol. 378(C).
    5. Huang, Chaochao & Wang, Chaoqian, 2024. "Memory-based involution dilemma on square lattices," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    6. Jiang, Yuan & Yan, Yuwei & Hong, Cheng & Yang, Songqing & Yu, Rongbin & Dai, Jiyang, 2022. "Multidirectional recovery strategy against failure," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    7. Lee, Hsuan-Wei & Cleveland, Colin & Szolnoki, Attila, 2023. "Group-size dependent synergy in heterogeneous populations," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    8. Lu, Shounan & Zhu, Ge & Dai, Jianhua, 2023. "Promoting effect of adaptive interaction based on random neighbors to cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 450(C).
    9. Han, Xu & Zhao, Xiaowei & Xia, Haoxiang, 2021. "Evolution of cooperation through aspiration-based adjustment of interaction range in spatial prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 393(C).
    10. Szolnoki, Attila & Chen, Xiaojie, 2020. "Gradual learning supports cooperation in spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    11. Wang, Chaoqian & Szolnoki, Attila, 2023. "Inertia in spatial public goods games under weak selection," Applied Mathematics and Computation, Elsevier, vol. 449(C).
    12. Wang, Si-Yi & Liu, Yan-Ping & Zhang, Feng & Wang, Rui-Wu, 2021. "Super-rational aspiration induced strategy updating promotes cooperation in the asymmetric prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    13. Szolnoki, Attila & Chen, Xiaojie, 2020. "Strategy dependent learning activity in cyclic dominant systems," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    14. Gao, Liyan & Pan, Qiuhui & He, Mingfeng, 2020. "Changeable updating rule promotes cooperation in well-mixed and structured populations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    15. Oliveira, B.F. de & Szolnoki, A., 2021. "Social dilemmas in off-lattice populations," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    16. Jia, Chun-Xiao & Liu, Run-Ran, 2022. "A moderate self-interest preference promotes cooperation in spatial public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    17. Wang, Le & Chen, Tong & Wu, Zhenghong, 2021. "Promoting cooperation by reputation scoring mechanism based on historical donations in public goods game," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    18. Xie, Kai & Liu, Xingwen & Wang, Huazhang & Jiang, Yulian, 2023. "Multi-heterogeneity public goods evolutionary game on lattice," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    19. Xie, Kai & Liu, Xingwen & Chen, Hao & Yang, Jun, 2022. "Preferential selection and expected payoff drive cooperation in spatial voluntary public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    20. Cui, Guang-Hai & Wang, Zhen & Li, Jun-Li & Jin, Xing & Zhang, Zhi-Wang, 2021. "Influence of precaution and dynamic post-indemnity based insurance policy on controlling the propagation of epidemic security risks in networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).

    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:phsmap:v:636:y:2024:i:c:s0378437124000529. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.