Optimal Supplier Selection Via Decision-Making Algorithmic Technique Based on Single-Valued Neutrosophic Fuzzy Hypersoft Set

Abstract

Hypersoft set, an extension of soft set, is more flexible and useful as it tackles the limitation of soft set for dealing with scenarios where distinct attributes are further classified into disjoint attribute-valued sets. It replaces single-argument approximate function of soft set with multi-argument approximate function. The main goal of this research is to align existing literature on single-valued neutrosophic fuzzy soft sets with the need for such a multi-argument function. Firstly, the novel notions of single-valued neutrosophic fuzzy hypersoft sets are characterized. Some of its essential basic properties and set theoretic operations are discussed with illustrated numerical examples. Secondly, fuzzy decision-making algorithm based on single-valued neutrosophic
fuzzy hypersoft set matrix is proposed. Explicatory application is presented which depicts the structural validity of proposed structure for successful application to the problems involving vagueness and uncertainties. Lastly, a comparison of the proposed structure with existing structures, is made under appropriate indicators.