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Interval-valued dual hesitant fuzzy prioritized aggregation operators based on Archimedean t-conorm and t-norm and their applications to multi-criteria decision making

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Języki publikacji
EN
Abstrakty
EN
Multi-criteria decision making (MCDM) technique and approach have been a trending topic in decision making and systems engineering to choosing the probable optimal options. The primary purpose of this article is to develop prioritized operators to multi-criteria decision making (MCDM) based on Archimedean t-conorm and t-norms (At-CN&t-Ns) under interval-valued dual hesitant fuzzy (IVDHF) environment. A new score function is defined for finding the rank of alternatives in MCDM problems with IVDHF information based on priority levels of criteria imposed by the decision maker. This paper introduces two aggregation operators: At-CN&t-N-based IVDHF prioritized weighted averaging (AIVDHFPWA), and weighted geometric (AIVDHFPWG) aggregation operators. Some of their desirable properties are also investigated in details. A methodology for prioritization-based MCDM is derived under IVDHF information. An illustrative example concerning MCDM problem about a Chinese university for appointing outstanding oversea teachers to strengthen academic education is considered. The method is also applicable for solving other real-life MCDM problems having IVDHF information.
Rocznik
Strony
213--247
Opis fizyczny
Bibliogr. 44 poz., rys., tab., wzory
Twórcy
autor
  • Department of Mathematics, Heramba Chandra College, Kolkata – 700029, India
  • Department of Mathematics, University of Kalyani, Kalyani – 741235, India
Bibliografia
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  • [7] B. Zhu, Z. Xu, and M. Xia: Dual Hesitant Fuzzy Sets, Journal of Applied Mathematics, 2012 (2012), 1-13.
  • [8] H. Wang, X. Zhao, and G. Wei: Dual hesitant fuzzy aggregation operators in multiple attribute decision making, Journal of Intelligent & Fuzzy Systems, 26 (2014) 2281-2290.
  • [9] Y. Ju, W. Zhang, and S. Yang: Some dual hesitant fuzzy Hamacher aggregation operators and their applications to multiple attribute decision making, Journal of Intelligent & Fuzzy Systems, 27 (2014), 2481-2495.
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  • [13] Y. Ju, X. Liu, and S. Yang: Interval-valued dual hesitant fuzzy aggregation operators and their applications to multiple attribute decision making, Journal of Intelligent & Fuzzy Systems, 27 (2014) 1203-1218.
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  • [15] W. Zhang, X. Li, and Y. Ju: Some Aggregation Operators Based on Einstein Operations under Interval-Valued Dual Hesitant Fuzzy Setting and Their Application, Mathematical Problems in Engineering, 2014 (2014), 1-21.
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  • [18] M. Xia, Z. Xu, and B. Zhu: Some issues on intuitionistic fuzzy aggregation operators based on Archimedean t-conorm and t-norm, Knowledge-Based Systems, 31 (2012), 78-88.
  • [19] Z. Zhang and C. Wu: Some interval-valued hesitant fuzzy aggregation operators based on Archimedean t-norm and t-conorm with their application in multi-criteria decision making, Journal of Intelligent & Fuzzy Systems, 27 (2014), 2737-2748.
  • [20] D. Yu: Archimedean Aggregation Operators Based on Dual Hesitant Fuzzy Set and Their Application to GDM, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 23 (2015), 761-780.
  • [21] A. Sarkar and A. Biswas: Multicriteria decision-making using Archimedean aggregation operators in Pythagorean hesitant fuzzy environment, International Journal of Intelligent Systems, 34 (2019), 1361-1386.
  • [22] A. Sarkar and A. Biswas: Development of Archimedean t-norm and t-conorm-based interval-valued dual hesitant fuzzy aggregation operators with their application in multicriteria decision making, Engineering Reports, 2020, DOI: 10.1002/eng2.12106.
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  • [25] Q. Yu, F. Hou, Y. Zhai, and Y. Du: Some Hesitant Fuzzy Einstein Aggregation Operators and Their Application to Multiple Attribute Group Decision Making, International Journal of Intelligent Systems, 31 (2016), 722-746.
  • [26] G. Wei: Hesitant fuzzy prioritized operators and their application to multiple attribute decision making, Knowledge-Based Systems, 31 (2012), 176-182.
  • [27] T. Y. Chen: A prioritized aggregation operator-based approach to multiple criteria decision making using interval-valued intuitionistic fuzzy sets: A comparative perspective, Information Sciences, 281(2014), 97-112.
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  • [29] J. Ye: Interval-Valued Hesitant Fuzzy Prioritized Weighted Aggregation Operators for Multiple Attribute Decision Making, Journal of Algorithms & Computational Technology, 8 (2014), 179-192.
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  • [31] Z. Ren and C. Wei: A multi-attribute decision-making method with prioritization relationship and dual hesitant fuzzy decision information, International Journal of Machine Learning and Cybernetics, 8 (2015), 755-763.
  • [32] A. Biswas and A. Sarkar: Development of dual hesitant fuzzy prioritized operators based on Einstein operations with their application to multicriteria group decision making, Archives of Control Sciences, 28(LXIV) (2018), 527-549.
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  • [37] M. Riaz and S.T. Tehrim: Cubic bipolar fuzzy ordered weighted geometric aggregation operators and their application using internal and external cubic bipolar fuzzy data, Computational and Applied Mathematics, 38 (2019).
  • [38] A. Biswas and B. Sarkar: Pythagorean fuzzy multicriteria group decision making through similarity measure based on point operators, International Journal of Intelligent Systems, 33 (2018), 1731-1744.
  • [39] A. Biswas and B. Sarkar: Pythagorean fuzzy TOPSIS for multicriteria group decision-making with unknown weight information through entropy measure, International Journal of Intelligent Systems, 34(2019), 1108-1128.
  • [40] B. Sarkar and A. Biswas: A unified method for Pythagorean fuzzy multicriteria group decision-making using entropy measure, linear programming and extended technique for ordering preference by similarity to ideal solution, Soft Computing, 24 (2020), 5333-5344.
  • [41] A. Biswas and B. Sarkar: Interval-valued Pythagorean fuzzy TODIM approach through point operator-based similarity measures for multicriteria group decision making, Kybernetes, 48 (2019), 496-519.
  • [42] B. Sarkar and A. Biswas: Pythagorean fuzzy AHP-TOPSIS integrated approach for transportation management through a new distance measure, Soft Computing, (2021), DOI: 10.1007/s00500-020-05433-2.
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-32e3371d-65a5-4333-8145-8bd5472bba49
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