IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v517y2019icp577-587.html
   My bibliography  Save this article

Robust optimal control of deterministic information epidemics with noisy transition rates

Author

Listed:
  • Liu, Fangzhou
  • Zhang, Zengjie
  • Buss, Martin

Abstract

In this paper the robust optimal control of deterministic information epidemics is inspected taking into consideration the noisy transition rates. Distinct from conventional works, the heterogeneous susceptible–infected–susceptible (SIS) model is adopted where both the heterogeneities in the network topology and the individual diversity are considered. In light of the commonly existing noise in the transition processes, we address the robust optimal control problem aiming at maximizing the spreading performance at the finite time instant given a fixed budget. By using the distribution analysis techniques, the inspected problem is transformed to a constrained optimal control problem and solved by the Pontryagin Maximum Principle (PMP). A novel approach combining the forward–backward sweep method and the secant method is proposed to efficiently reduce the computation burden. The performance of the robust optimal control as well as the influence of the parameters is examined by numerical experiments in real social networks.

Suggested Citation

  • Liu, Fangzhou & Zhang, Zengjie & Buss, Martin, 2019. "Robust optimal control of deterministic information epidemics with noisy transition rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 577-587.
    • Handle: RePEc:eee:phsmap:v:517:y:2019:i:c:p:577-587
    DOI: 10.1016/j.physa.2018.11.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118314420
    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.2018.11.025?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. Michael McAsey & Libin Mou & Weimin Han, 2012. "Convergence of the forward-backward sweep method in optimal control," Computational Optimization and Applications, Springer, vol. 53(1), pages 207-226, September.
    2. Nikolaos Askitas, 2017. "Explaining opinion polarisation with opinion copulas," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-11, August.
    3. Liu, Yun & Diao, Su-Meng & Zhu, Yi-Xiang & Liu, Qing, 2016. "SHIR competitive information diffusion model for online social media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 543-553.
    4. repec:hal:pseose:hal-00812894 is not listed on IDEAS
    5. Qu, Bo & Wang, Huiijuan, 2017. "SIS epidemic spreading with correlated heterogeneous infection rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 13-24.
    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. Lv, Wei & He, Hanfei & Li, Kezan, 2022. "Robust optimal control of a network-based SIVS epidemic model with time delay," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    2. Wang, Zhixiao & Rui, Xiaobin & Yuan, Guan & Cui, Jingjing & Hadzibeganovic, Tarik, 2021. "Endemic information-contagion outbreaks in complex networks with potential spreaders based recurrent-state transmission dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).

    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. Alessandro Ramponi & Maria Elisabetta Tessitore, 2024. "Optimal Social and Vaccination Control in the SVIR Epidemic Model," Mathematics, MDPI, vol. 12(7), pages 1-17, March.
    2. Niyirora, Jerome & Zhuang, Jun, 2017. "Fluid approximations and control of queues in emergency departments," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1110-1124.
    3. La Torre, Davide & Liuzzi, Danilo & Marsiglio, Simone, 2021. "Epidemics and macroeconomic outcomes: Social distancing intensity and duration," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    4. Yi, Yinxue & Zhang, Zufan & Gan, Chenquan, 2018. "The effect of social tie on information diffusion in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 783-794.
    5. Akinlotan, Morenikeji Deborah & Mallet, Daniel G. & Araujo, Robyn P., 2020. "An optimal control model of the treatment of chronic Chlamydia trachomatis infection using a combination treatment with antibiotic and tryptophan," Applied Mathematics and Computation, Elsevier, vol. 375(C).
    6. Tian, Xiaohong & Xu, Rui & Lin, Jiazhe, 2019. "Mathematical analysis of a cholera infection model with vaccination strategy," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 517-535.
    7. Jiaqi Liu & Jiayin Qi, 2022. "Online Public Rumor Engagement Model and Intervention Strategy in Major Public Health Emergencies: From the Perspective of Social Psychological Stress," IJERPH, MDPI, vol. 19(4), pages 1-22, February.
    8. Alessandro Ramponi & Maria Elisabetta Tessitore, 2022. "The economic cost of social distancing during a pandemic: an optimal control approach in the SVIR model," Papers 2208.04908, arXiv.org.
    9. Wang, Jinling & Jiang, Haijun & Hu, Cheng & Yu, Zhiyong & Li, Jiarong, 2021. "Stability and Hopf bifurcation analysis of multi-lingual rumor spreading model with nonlinear inhibition mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    10. Bruno Buonomo, 2015. "Modeling ITNs Usage: Optimal Promotion Programs Versus Pure Voluntary Adoptions," Mathematics, MDPI, vol. 3(4), pages 1-14, December.
    11. Rui, Xiaobin & Meng, Fanrong & Wang, Zhixiao & Yuan, Guan & Du, Changjiang, 2018. "SPIR: The potential spreaders involved SIR model for information diffusion in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 254-269.
    12. Wang, Zhixiao & Rui, Xiaobin & Yuan, Guan & Cui, Jingjing & Hadzibeganovic, Tarik, 2021. "Endemic information-contagion outbreaks in complex networks with potential spreaders based recurrent-state transmission dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    13. Zhang, Yaming & Su, Yanyuan & Weigang, Li & Liu, Haiou, 2018. "Rumor and authoritative information propagation model considering super spreading in complex social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 395-411.
    14. Xu, Jinghong & Du, Zhitao & Guo, Jianchao & Fu, Xiangling & Zhang, Yuqiang & Wu, Ye, 2018. "Empirical and modeling studies of WeChat information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1113-1120.
    15. Wan, Chen & Li, Tao & Zhang, Wu & Dong, Jing, 2018. "Dynamics of epidemic spreading model with drug-resistant variation on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 17-28.
    16. Torre, Davide La & Liuzzi, Danilo & Marsiglio, Simone, 2021. "Transboundary pollution externalities: Think globally, act locally?," Journal of Mathematical Economics, Elsevier, vol. 96(C).
    17. Jia, Peng & Liu, Jiayong & Fang, Yong & Liu, Liang & Liu, Luping, 2018. "Modeling and analyzing malware propagation in social networks with heterogeneous infection rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 240-254.
    18. Ma, Jing & Zhu, He, 2018. "Rumor diffusion in heterogeneous networks by considering the individuals’ subjective judgment and diverse characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 276-287.
    19. Fu, Guiyuan & Chen, Feier & Liu, Jianguo & Han, Jingti, 2019. "Analysis of competitive information diffusion in a group-based population over social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 409-419.
    20. Wang, Chuanbiao & Liu, Ruiying & Wang, Yan, 2023. "The spread dynamics model of the interaction between rumors and derivative rumors in emergencies under the control strategy," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).

    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:517:y:2019:i:c:p:577-587. 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.