Hybrid Decision-Making Frameworks under Complex Spherical Fuzzy N-Soft Sets. (23rd March 2021)

• Record Type: Journal Article
• Authors: Akram, Muhammad; Shabir, Maria; Al-Kenani, Ahmad N.; Alcantud, José Carlos R.
• Other Names: Khan Sami Ullah Academic Editor.
• Is Part Of: Journal of mathematics. Volume 2021(2021)
• Publication Date: 2021-03-23
• Subjects: Mathematics -- Periodicals; Mathematics; Periodicals; 510
• DOI: 10.1155/2021/5563215
• Languages: English
• ISSNs: 2314-4629

Abstract

Abstract : This paper presents the novel concept of complex spherical fuzzy N -soft set (C S F N S f S ) which is capable of handling two-dimensional vague information with parameterized ranking systems. First, we propose the basic notions for a theoretical development of C S F N S f S s, including ranking functions, comparison rule, and fundamental operations (complement, union, intersection, sum, and product). Furthermore, we look into some properties of C S F N S f S s . We then produce three algorithms for multiattribute decision-making that take advantage of these elements. We demonstrate their applicability with the assistance of a numerical problem (selection of best third-party app of the year). A comparison with the performance of Pythagorean N -soft sets speaks for the superiority of our approach. Moreover, with an aim to expand the range of techniques for multiattribute group decision-making problems, we design a C S F N S f -TOPSIS method. We use a complex spherical fuzzy N -soft weighted average operator in order to aggregate the decisions of all experts according to the power of the attributes and features of alternatives. We present normalized-Euclidean distances (from the alternatives to both the C S F N S f positive and negative ideal solutions, respectively) and revised closeness index in order to produce a best feasible alternative. As an illustration, we design a mathematical model for the selection of the best physiotherapist doctor of Mayo hospital, Lahore. We conduct a comparison with the existing complex spherical fuzzy TOPSIS method that confirms the stability of the proposed model and the reliability of its results.