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Article type: Research Article
Authors: Dhumras, Himanshu | Bajaj, Rakesh Kumar; *
Affiliations: Department of Mathematics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India
Correspondence: [*] Corresponding author. Rakesh K Bajaj. E-mail: rakesh.bajaj@gmail.com.
Abstract: Systematic assessment of insufficiencies and inexactness in the information along with parametrization of multi-sub attributes is one of the substantial features in the field of decision-making. In the present communication, a new way of defining Picture Fuzzy Hypersoft Set (PFHSS) has been presented which contains an additional capacity of accommodating the components of neutral membership (abstain) and refusal compared to Intuionistic Fuzzy Hypersoft Set (IFHSS). The main objective of the present study is to establish the novelty of PFHSS with some of the basic operations and introduce various important aggregation operators. Some of the important properties and operational laws related to the introduced picture fuzzy hypersoft weighted average/ordered weighted average operator (PFHSWA/PFHSOWA) and weighted geometric/ordered weighted geometric operator (PFHSWG/PFHSOWG) have been proved in detail. On the basis of these aggregation operators and obtained results, a new algorithm for solving a decision-making problem, involving the multi-sub attributes and their parametrization in the shade of abstain and refusal feature, has been proposed. A numerical example of the selection process of employees for a company has been solved in order to suitably ensure and validate the implementation of the proposed methodology. Some of the advantageous features of the proposed notions and algorithm have been listed along with the comparative analysis in contrast with the existing literature. Finally, the efficacy of the proposed notion and methodology has been duly concluded with the scope for future work.
Keywords: Picture fuzzy set, soft set, hypersoft set, aggregation operators, decision-making
DOI: 10.3233/JIFS-222437
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7419-7447, 2023
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