IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i21p2764-d669200.html
   My bibliography  Save this article

Research of NP-Complete Problems in the Class of Prefractal Graphs

Author

Listed:
  • Rasul Kochkarov

    (Department of Data Analysis and Machine Learning, Faculty of Information Technology and Big Data Analysis, Financial University under the Government of the Russian Federation, Leningradsky Prospekt, 49, 125993 Moscow, Russia)

Abstract

NP-complete problems in graphs, such as enumeration and the selection of subgraphs with given characteristics, become especially relevant for large graphs and networks. Herein, particular statements with constraints are proposed to solve such problems, and subclasses of graphs are distinguished. We propose a class of prefractal graphs and review particular statements of NP-complete problems. As an example, algorithms for searching for spanning trees and packing bipartite graphs are proposed. The developed algorithms are polynomial and based on well-known algorithms and are used in the form of procedures. We propose to use the class of prefractal graphs as a tool for studying NP-complete problems and identifying conditions for their solvability. Using prefractal graphs for the modeling of large graphs and networks, it is possible to obtain approximate solutions, and some exact solutions, for problems on natural objects—social networks, transport networks, etc.

Suggested Citation

  • Rasul Kochkarov, 2021. "Research of NP-Complete Problems in the Class of Prefractal Graphs," Mathematics, MDPI, vol. 9(21), pages 1-20, October.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:21:p:2764-:d:669200
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/21/2764/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/21/2764/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guan, Jihong & Wu, Yuewen & Zhang, Zhongzhi & Zhou, Shuigeng & Wu, Yonghui, 2009. "A unified model for Sierpinski networks with scale-free scaling and small-world effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2571-2578.
    2. Komjáthy, Júlia & Simon, Károly, 2011. "Generating hierarchial scale-free graphs from fractals," Chaos, Solitons & Fractals, Elsevier, vol. 44(8), pages 651-666.
    3. Hwangbo, Soonho & Heo, SungKu & Yoo, ChangKyoo, 2022. "Development of deterministic-stochastic model to integrate variable renewable energy-driven electricity and large-scale utility networks: Towards decarbonization petrochemical industry," Energy, Elsevier, vol. 238(PC).
    4. Gong, Helin & Jin, Xian’an, 2017. "A general method for computing Tutte polynomials of self-similar graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 117-129.
    5. Criado-Alonso, Ángeles & Battaner-Moro, Elena & Aleja, David & Romance, Miguel & Criado, Regino, 2021. "Enriched line graph: A new structure for searching language collocations," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    6. Jun-Ho Huh & Jimin Hwa & Yeong-Seok Seo, 2020. "Hierarchical System Decomposition Using Genetic Algorithm for Future Sustainable Computing," Sustainability, MDPI, vol. 12(6), pages 1-32, March.
    7. Moreno-Pulido, Soledad & Pavón-Domínguez, Pablo & Burgos-Pintos, Pedro, 2021. "Temporal evolution of multifractality in the Madrid Metro subway network," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    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. Rasul Kochkarov & Azret Kochkarov, 2022. "Introduction to the Class of Prefractal Graphs," Mathematics, MDPI, vol. 10(14), pages 1-17, July.
    2. Zeng, Cheng & Xue, Yumei & Huang, Yuke, 2021. "Fractal networks with Sturmian structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    3. Hamed, Mohammad M. & Mohammed, Ali & Olabi, Abdul Ghani, 2023. "Renewable energy adoption decisions in Jordan's industrial sector: Statistical analysis with unobserved heterogeneity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    4. Huang, Liang & Zheng, Yu, 2023. "Asymptotic formula on APL of fractal evolving networks generated by Durer Pentagon," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    5. Feng, Qunqiang & Li, Xing & Hu, Zhishui, 2023. "Asymptotic degree distribution in a homogeneous evolving network model," Statistics & Probability Letters, Elsevier, vol. 193(C).
    6. Xi, Lifeng & Wang, Lihong & Wang, Songjing & Yu, Zhouyu & Wang, Qin, 2017. "Fractality and scale-free effect of a class of self-similar networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 31-40.
    7. Le, Anbo & Gao, Fei & Xi, Lifeng & Yin, Shuhua, 2015. "Complex networks modeled on the Sierpinski gasket," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 646-657.
    8. Ye, Dandan & Dai, Meifeng & Sun, Yu & Su, Weiyi, 2017. "Average weighted receiving time on the non-homogeneous double-weighted fractal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 390-402.
    9. Dai, Meifeng & Shao, Shuxiang & Su, Weiyi & Xi, Lifeng & Sun, Yanqiu, 2017. "The modified box dimension and average weighted receiving time of the weighted hierarchical graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 475(C), pages 46-58.
    10. Haroon ur Rashid Khan & Usama Awan & Khalid Zaman & Abdelmohsen A. Nassani & Mohamed Haffar & Muhammad Moinuddin Qazi Abro, 2021. "Assessing Hybrid Solar-Wind Potential for Industrial Decarbonization Strategies: Global Shift to Green Development," Energies, MDPI, vol. 14(22), pages 1-14, November.
    11. Zhang, Qian & Xue, Yumei & Wang, Daohua & Niu, Min, 2019. "Asymptotic formula on average path length in a hierarchical scale-free network with fractal structure," Chaos, Solitons & Fractals, Elsevier, vol. 122(C), pages 196-201.
    12. Huang, Yuke & Zhang, Hanxiong & Zeng, Cheng & Xue, Yumei, 2020. "Scale-free and small-world properties of a multiple-hub network with fractal structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    13. Criado-Alonso, Ángeles & Aleja, David & Romance, Miguel & Criado, Regino, 2022. "Derivative of a hypergraph as a tool for linguistic pattern analysis," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    14. Liao, Yunhua & Aziz-Alaoui, M.A. & Zhao, Junchan & Hou, Yaoping, 2019. "The behavior of Tutte polynomials of graphs under five graph operations and its applications," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    15. Chen, Jin & Le, Anbo & Wang, Qin & Xi, Lifeng, 2016. "A small-world and scale-free network generated by Sierpinski Pentagon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 126-135.
    16. He, Jia & Xue, Yumei, 2018. "Scale-free and small-world properties of hollow cube networks," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 11-15.
    17. Carletti, Timoteo & Righi, Simone, 2010. "Weighted Fractal Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2134-2142.
    18. Wang, Daohua & Zeng, Cheng & Zhao, Zixuan & Wu, Zhiqiang & Xue, Yumei, 2023. "Kirchhoff index of a class of polygon networks," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    19. Wang, Songjing & Xi, Lifeng & Xu, Hui & Wang, Lihong, 2017. "Scale-free and small-world properties of Sierpinski networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 690-700.
    20. Lu, Zhe-Ming & Su, Yu-Xin & Guo, Shi-Ze, 2013. "Deterministic scale-free small-world networks of arbitrary order," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3555-3562.

    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:gam:jmathe:v:9:y:2021:i:21:p:2764-:d:669200. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.