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Security Risks to Petroleum Industry: An Innovative Modeling Technique Based on Novel Concepts of Complex Bipolar Fuzzy Information

Author

Listed:
  • Abdul Nasir

    (Department of Mathematics, Institute of Numerical Sciences, Gomal University, Dera Ismail Khan 29050, Pakistan)

  • Naeem Jan

    (Department of Mathematics, Institute of Numerical Sciences, Gomal University, Dera Ismail Khan 29050, Pakistan)

  • Miin-Shen Yang

    (Department of Applied Mathematics, Chung Yuan Christian University, Chung-Li, Taoyuan 32023, Taiwan)

  • Dragan Pamucar

    (Department of Logistics, Military Academy, The University of Defense in Belgrade, 11000 Belgrade, Serbia)

  • Dragan Marinkovic

    (Department of Structural Analysis, Faculty of Mechanical Engineering and Transport Systems, Technische Universität Berlin, 10623 Berlin, Germany
    Department of Transport and Logistics, Faculty of Mechanical Engineering, University of Nis, 18000 Nis, Serbia)

  • Sami Ullah Khan

    (Department of Mathematics, Institute of Numerical Sciences, Gomal University, Dera Ismail Khan 29050, Pakistan)

Abstract

In today’s world, the countries that have easy access to energy resources are economically strong, and thus, maintaining a better geopolitical position is important. Petroleum products such as gas and oil are currently the leading energy resources. Due to their excessive worth, the petroleum industries face many risks and security threats. Observing the nature of such problems, it is asserted that the complex bipolar fuzzy information is a better choice for modeling them. Keeping the said problem in mind, this article introduces the novel structure of complex bipolar fuzzy relation (CBFR), which is basically used to find out the relationships between complex bipolar fuzzy sets (CBFSs). Similarly, the types of CBFRs are also defined, which is helpful during the process of analyzing and interpreting the problem. Moreover, some useful results and interesting properties of the proposed structures are deliberated. Further, a new modeling technique based on the proposed structures is initiated, which is used to investigate the security risks to petroleum industries. Furthermore, a detailed comparative analysis proves the advantages and supremacy of CBFRs over other structures. Therefore, the results achieved by the proposed methods are substantially reliable, practical and complete.

Suggested Citation

  • Abdul Nasir & Naeem Jan & Miin-Shen Yang & Dragan Pamucar & Dragan Marinkovic & Sami Ullah Khan, 2022. "Security Risks to Petroleum Industry: An Innovative Modeling Technique Based on Novel Concepts of Complex Bipolar Fuzzy Information," Mathematics, MDPI, vol. 10(7), pages 1-26, March.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:7:p:1067-:d:779968
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    References listed on IDEAS

    as
    1. Zeeshan Ali & Tahir Mahmood & Miin-Shen Yang, 2020. "TOPSIS Method Based on Complex Spherical Fuzzy Sets with Bonferroni Mean Operators," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    2. Shuker Khalil & Ahmed Hassan & Haya Alaskar & Wasiq Khan & Abir Hussain, 2021. "Fuzzy Logical Algebra and Study of the Effectiveness of Medications for COVID-19," Mathematics, MDPI, vol. 9(22), pages 1-12, November.
    Full references (including those not matched with items on IDEAS)

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