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Article type: Research Article
Authors: Akram, Muhammada | Shahzadi, Gulfama | Shahzadi, Sundasb; *
Affiliations: [a] Department of Mathematics, University of the Punjab, New Campus, Lahore, Pakistan | [b] Department of Mathematics, Division of Science and Technology, University of Education, Lahore, Pakistan
Correspondence: [*] Corresponding author. Sundas Shahzadi, Department of Mathematics, Division of Science and Technology, University of Education, Lahore, Pakistan. E-mail: [email protected].
Abstract: An q-rung orthopair fuzzy set is a generalized structure that covers the modern extensions of fuzzy set, including intuitionistic fuzzy set and Pythagorean fuzzy set, with an adjustable parameter q that makes it flexible and adaptable to describe the inexact information in decision making. The condition of q-rung orthopair fuzzy set, i.e., sum of qth power of membership degree and nonmembership degree is bounded by one, makes it highly competent and adequate to get over the limitations of existing models. The basic purpose of this study is to establish some aggregation operators under the q-rung orthopair fuzzy environment with Einstein norm operations. Motivated by innovative features of Einstein operators and dominant behavior of q-rung orthopair fuzzy set, some new aggregation operators, namely, q-rung orthopair fuzzy Einstein weighted averaging, q-rung orthopair fuzzy Einstein ordered weighted averaging, generalized q-rung orthopair fuzzy Einstein weighted averaging and generalized q-rung orthopair fuzzy Einstein ordered weighted averaging operators are defined. Furthermore, some properties related to proposed operators are presented. Moreover, multi-attribute decision making problems related to career selection, agriculture land selection and residential place selection are presented under these operators to show the capability and proficiency of this new idea. The comparison analysis with existing theories shows the superiorities of proposed model.
Keywords: Einstein operators, q-rung orthopair fuzzy numbers, averaging operators, generalized weighted averaging operators
DOI: 10.3233/JIFS-201611
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 3, pp. 4779-4798, 2021
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