Neutrosophic Hypersoft Expert Set: Theory and Applications

Abstract

Soft set-like models deal with single argument approximate functions while hypersoft set, an extension of the soft set, deals with multi-argument approximate functions. The soft set cannot handle situations when attributes are required to be further divided into disjoint attribute-valued sets. To overcome this situation, a hypersoft set has been developed. In different fields like decision making and medical diagnosis, many researchers developed models based on the soft set for the solution of many problems. But these models deal with only one expert who creates many problems for the users, primarily in designing questionnaires. To remove this discrepancy, we present a neutrosophic hypersoft expert set. This model not only solves the problem of dealing with one expert but also solves the problem of different parametric-valued sets parallel to different characteristics. In this study, we first introduce the concept of neutrosophic hypersoft expert sets, which is a amalgam of both structures i.e., neutrosophic set and hypersoft expert sets. Certain essential basic characteristics (i.e., subset, equal set, agree, disagree set, null set, whole relative set, and whole absolute set), aggregation operations (i.e., complement, restricted union, extended intersection, AND and OR ), and results (i.e., idempotent, absorption, domination, identity, commutative, associative and distributive law ) are discussed with examples. Some hybrid structures of the neutrosophic hypersoft expert set are developed with illustrated examples. In the end, a decision-making application is presented for the validity of the proposed theory.