Abstract

In this paper, we set forth a framework for solving a multiattribute group decision-making (MAGDM) problem, namely, the selection of a firm for participation in a Saudi oil refinery project in Pakistan. This project will prove a key success factor for the economic growth of Pakistan due to its enormous economic impact on the energy sector, industrial development, commerce, transportation, and so on. This multiplicity justifies that several intricate components comprising both intrinsic and external attributes should be adequately evaluated for the selection of such a firm, that is, the formulation of this question as a MAGDM problem. Nonbinary evaluation with two-dimensional ambiguity and uncertainty in the parameters are general concerns in modern literature, and they fit into this problem. Within this context, one of the most superior and amenable theories (complex spherical fuzzy N -soft sets, henceforth C S F N S f S s ) shall be used to formulate a new comprehensive method, known as complex spherical fuzzy N -soft-VIKOR ( C S F N S f -VIKOR) method. According to the general spirit of the benchmark technique, the normalized Euclidean distances and the weights of the attributes are jointly handled, and as consequence, two main features (“maximum group utility” and “minimum individual regret”) are acquired. The coefficient strategy with reference to group utility measure and individual regret measure of opponents are employed for the compromise measure. Armed with this novel tool, we single out the most feasible firm according to the preference order of the alternatives examined by the decision-makers on the subject of linear normalized weights of experts and attributes. Furthermore, a comparative analysis justifies the C S F -VIKOR method, and some results prove its capabilities and validity. Moreover, a sensitivity test certifies the stability of the proposed method.

Highlights

  • In 1998, the VIKOR approach was drafted by Opricovic [1] as a multiattribute decision-making (MADM) method

  • E main aim of our proposed idea is to develop the methodology of VIKOR within the hybrid model of complex spherical fuzzy N-soft set (CSFNSfS) for the solution of multiattribute group decision-making (MAGDM) problems precisely. e contributions of this paper are as follows: (i) We introduce a hybrid MAGDM VIKOR approach whose structure is based on CSFNSfSs, and it is known as CSFNSf-VIKOR technique. is methodology qualifies for situations that comprise parameterized ranking information; it successfully evaluates a large proportion of existing MAGDM problems, as well as decision-making problems with nonbinary parameterized information as an initial assessment

  • A hybrid decision-making model has been introduced in this paper, which is based on the VIKOR method but allows us to solve problems posed in the elaborate form of complex spherical fuzzy N-soft sets. is model was developed by Akram et al [34]

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Summary

A Multiattribute Decision-Making Framework

Received 3 July 2021; Revised 4 August 2021; Accepted 12 August 2021; Published 31 August 2021. Nonbinary evaluation with two-dimensional ambiguity and uncertainty in the parameters are general concerns in modern literature, and they fit into this problem. Within this context, one of the most superior and amenable theories (complex spherical fuzzy N-soft sets, CSFNSfSs) shall be used to formulate a new comprehensive method, known as complex spherical fuzzy N-soft-VIKOR (CSFNSf-VIKOR) method. E coefficient strategy with reference to group utility measure and individual regret measure of opponents are employed for the compromise measure Armed with this novel tool, we single out the most feasible firm according to the preference order of the alternatives examined by the decision-makers on the subject of linear normalized weights of experts and attributes. A sensitivity test certifies the stability of the proposed method

Introduction
Complex Spherical Fuzzy N-Soft Sets
Aggregated Complex Spherical Fuzzy N-Soft Performance
Application to Group Decision-Making
Sensitivity Test
Advantages of Proposed Method
Conclusion
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