An Inclusive Study on Fundamentals of Hypersoft Expert Set with Application

Abstract

Soft set deals with single set of attributes whereas its extension hypersoft set deals with multi attribute-valued disjoint sets corresponding to distinct attributes. Many researchers have created some models based on soft set to solve problems in decision-making, but most of these models deal with only one expert. This causes a problem with the users, especially with those who use questionnaires in their work. Therefore we present a novel model hypersoft expert set which not only addresses this limitation of soft-like models with the emphasis on the opinion of all experts but also resolves the inadequacy of soft set for attribute-valued disjoint sets corresponding to distinct attributes. In this study, the existing concept of hypersoft expert set is modified and some fundamental properties i.e. subset, not set and equal set, whole set, absolute set, relative null set, relative absolute set; results i.e. commutative, associative, distributive and De’ Morgan’s Laws and set-theoretic operations i.e. complement, union intersection, restricted union, extended intersection, AND, and OR are developed. An algorithm is proposed to solve decision-making problem and applied to recruitment process for hiring ”right person for the right job”.