IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v8y2020i6p1008-d373628.html
   My bibliography  Save this article

An Extension of Fuzzy Competition Graph and Its Uses in Manufacturing Industries

Author

Listed:
  • Tarasankar Pramanik

    (Department of Mathematics, Khanpur Gangche High School, Paschim Medinipur 721201, India
    These authors contributed equally to this work.)

  • G. Muhiuddin

    (Department of Mathematics, University of Tabuk, Tabuk 71491, Saudi Arabia
    These authors contributed equally to this work.)

  • Abdulaziz M. Alanazi

    (Department of Mathematics, University of Tabuk, Tabuk 71491, Saudi Arabia
    These authors contributed equally to this work.)

  • Madhumangal Pal

    (Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore 721102, Inida
    These authors contributed equally to this work.)

Abstract

Competition graph is a graph which constitutes from a directed graph (digraph) with an edge between two vertices if they have some common preys in the digraph. Moreover, Fuzzy competition graph (briefly, FCG) is the higher extension of the crisp competition graph by assigning fuzzy value to each vertex and edge. Also, Interval-valued FCG (briefly, IVFCG) is another higher extension of fuzzy competition graph by taking each fuzzy value as a sub-interval of the interval [ 0 , 1 ] . This graph arises in many real world systems; one of them is discussed as follows: Each and every species in nature basically needs ecological balance to survive. The existing species depends on one another for food. If there happens any extinction of any species, there must be a crisis of food among those species which depend on that extinct species. The height of food crisis among those species varies according to their ecological status, environment and encompassing atmosphere. So, the prey to prey relationship among the species cannot be assessed exactly. Therefore, the assessment of competition of species is vague or shadowy. Motivated from this idea, in this paper IVFCG is introduced and several properties of IVFCG and its two variants interval-valued fuzzy k -competition graphs (briefly, IVFKCG) and interval-valued fuzzy m -step competition graphs (briefly, IVFMCG) are presented. The work is helpful to assess the strength of competition among competitors in the field of competitive network system. Furthermore, homomorphic and isomorphic properties of IVFCG are also discussed. Finally, an appropriate application of IVFCG in the competition among the production companies in market is presented to highlight the relevance of IVFCG.

Suggested Citation

  • Tarasankar Pramanik & G. Muhiuddin & Abdulaziz M. Alanazi & Madhumangal Pal, 2020. "An Extension of Fuzzy Competition Graph and Its Uses in Manufacturing Industries," Mathematics, MDPI, vol. 8(6), pages 1-23, June.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:6:p:1008-:d:373628
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/8/6/1008/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/8/6/1008/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Deveci, Muhammet & Cali, Umit & Kucuksari, Sadik & Erdogan, Nuh, 2020. "Interval type-2 fuzzy sets based multi-criteria decision-making model for offshore wind farm development in Ireland," Energy, Elsevier, vol. 198(C).
    2. Sovan Samanta & Madhumangal Pal, 2013. "Fuzzy k-competition graphs and p-competition fuzzy graphs," Fuzzy Information and Engineering, Springer, vol. 5(2), pages 191-204, June.
    3. Changiz Eslahchi & B. N. Onagh, 2006. "Vertex-strength of fuzzy graphs," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2006, pages 1-9, 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. Liu, Xinglei & Liu, Jun & Ren, Kezheng & Liu, Xiaoming & Liu, Jiacheng, 2022. "An integrated fuzzy multi-energy transaction evaluation approach for energy internet markets considering judgement credibility and variable rough precision," Energy, Elsevier, vol. 261(PB).
    2. Yuzgec, Ugur & Dokur, Emrah & Balci, Mehmet, 2024. "A novel hybrid model based on Empirical Mode Decomposition and Echo State Network for wind power forecasting," Energy, Elsevier, vol. 300(C).
    3. Aleksandar Aleksić & Danijela Tadić, 2023. "Industrial and Management Applications of Type-2 Multi-Attribute Decision-Making Techniques Extended with Type-2 Fuzzy Sets from 2013 to 2022," Mathematics, MDPI, vol. 11(10), pages 1-24, May.
    4. Bartłomiej Kizielewicz & Jarosław Wątróbski & Wojciech Sałabun, 2020. "Identification of Relevant Criteria Set in the MCDA Process—Wind Farm Location Case Study," Energies, MDPI, vol. 13(24), pages 1-40, December.
    5. Dounia El Bourakadi & Hiba Ramadan & Ali Yahyaouy & Jaouad Boumhidi, 2023. "A robust energy management approach in two-steps ahead using deep learning BiLSTM prediction model and type-2 fuzzy decision-making controller," Fuzzy Optimization and Decision Making, Springer, vol. 22(4), pages 645-667, December.
    6. Lu, Zhiming & Gao, Yan & Xu, Chuanbo, 2021. "Evaluation of energy management system for regional integrated energy system under interval type-2 hesitant fuzzy environment," Energy, Elsevier, vol. 222(C).
    7. Dokur, Emrah & Erdogan, Nuh & Salari, Mahdi Ebrahimi & Karakuzu, Cihan & Murphy, Jimmy, 2022. "Offshore wind speed short-term forecasting based on a hybrid method: Swarm decomposition and meta-extreme learning machine," Energy, Elsevier, vol. 248(C).
    8. Muhammad Akram & Musavarah Sarwar, 2018. "New Applications of m-Polar Fuzzy Competition Graphs," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 14(02), pages 249-276, July.
    9. Gang Kou & Özlem Olgu Akdeniz & Hasan Dinçer & Serhat Yüksel, 2021. "Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-28, December.
    10. Ziemba, Paweł, 2022. "Uncertain Multi-Criteria analysis of offshore wind farms projects investments – Case study of the Polish Economic Zone of the Baltic Sea," Applied Energy, Elsevier, vol. 309(C).
    11. Zhang, Hua & Li, Zongkun & Ge, Wei & Zhang, Yadong & Wang, Te & Sun, Heqiang & Jiao, Yutie, 2024. "An extended Bayesian network model for calculating dam failure probability based on fuzzy sets and dynamic evidential reasoning," Energy, Elsevier, vol. 301(C).
    12. Konstantinos Kokkinos & Vayos Karayannis, 2020. "Supportiveness of Low-Carbon Energy Technology Policy Using Fuzzy Multicriteria Decision-Making Methodologies," Mathematics, MDPI, vol. 8(7), pages 1-26, July.
    13. Liu, Jicheng & Lu, Yunyuan, 2023. "A task matching model of photovoltaic storage system under the energy blockchain environment - based on GA-CLOUD-GS algorithm," Energy, Elsevier, vol. 283(C).
    14. Zhao, Chengxuan & Yang, Xiao & Yu, Jie & Yang, Minghan & Wang, Jianye & Chen, Shuai, 2023. "Interval type-2 fuzzy logic control for a space nuclear reactor core power system," Energy, Elsevier, vol. 280(C).
    15. Sahil Kashyap & Bartosz Paradowski & Neeraj Gandotra & Namita Saini & Wojciech Sałabun, 2024. "A Novel Trigonometric Entropy Measure Based on the Complex Proportional Assessment Technique for Pythagorean Fuzzy Sets," Energies, MDPI, vol. 17(2), pages 1-18, January.
    16. Men, Jinkun & Zhao, Chunmeng, 2024. "A Type-2 fuzzy hybrid preference optimization methodology for electric vehicle charging station location," Energy, Elsevier, vol. 293(C).
    17. Ghulam Muhiuddin & Sovan Samanta & Abdulrahman F. Aljohani & Abeer M. Alkhaibari, 2023. "A Study on Graph Centrality Measures of Different Diseases Due to DNA Sequencing," Mathematics, MDPI, vol. 11(14), pages 1-18, July.
    18. Malinka Ivanova & Mariana Durcheva, 2023. "M-Polar Fuzzy Graphs and Deep Learning for the Design of Analog Amplifiers," Mathematics, MDPI, vol. 11(4), pages 1-16, February.
    19. Amna Habib & Muhammad Akram & Adeel Farooq, 2019. "q -Rung Orthopair Fuzzy Competition Graphs with Application in the Soil Ecosystem," Mathematics, MDPI, vol. 7(1), pages 1-33, January.
    20. Paweł Ziemba, 2021. "Multi-Criteria Fuzzy Evaluation of the Planned Offshore Wind Farm Investments in Poland," Energies, MDPI, vol. 14(4), pages 1-19, February.

    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:8:y:2020:i:6:p:1008-:d:373628. 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.