Abstract
Neutrosophic triplet structure yields a symmetric property of truth membership on the left, indeterminacy membership in the centre and false membership on the right, as do points of object, centre and image of reflection. As an extension of a neutrosophic set, the Q-neutrosophic set was introduced to handle two-dimensional uncertain and inconsistent situations. We extend the soft expert set to generalized Q-neutrosophic soft expert set by incorporating the idea of soft expert set to the concept of Q-neutrosophic set and attaching the parameter of fuzzy set while defining a Q-neutrosophic soft expert set. This pattern carries the benefits of Q-neutrosophic sets and soft sets, enabling decision makers to recognize the views of specialists with no requirement for extra lumbering tasks, thus making it exceedingly reasonable for use in decision-making issues that include imprecise, indeterminate and inconsistent two-dimensional data. Some essential operations namely subset, equal, complement, union, intersection, AND and OR operations and additionally several properties relating to the notion of generalized Q-neutrosophic soft expert set are characterized. Finally, an algorithm on generalized Q-neutrosophic soft expert set is proposed and applied to a real-life example to show the efficiency of this notion in handling such problems.
Highlights
Zadeh established the concept of fuzzy set [1] as a way to handle uncertain information, by assigning a number to each element that shows the degree of membership of the element.Intuitionistic fuzzy set [2] is another way to handle uncertainty that assigns two numbers to each element
These concepts are widely applicable to different life branches, they lack the ability to handle two-dimensional problems. This motivates the definition of Q-fuzzy soft set [11,12] that served the uncertainty and two-dimensionality simultaneously. This was extended to the theory of Q-neutrosophic soft set (Q-NSS) [13] by extending the theory of Q-fuzzy soft set to a neutrosophic set
We review some basic ideas of soft set, neutrosophic set and Q-neutrosophic soft expert set that are related to the study in this work
Summary
Zadeh established the concept of fuzzy set [1] as a way to handle uncertain information, by assigning a number to each element that shows the degree of membership of the element. It has been extended extensively to fuzzy soft set [6], vague soft set [7,8,9] and neutrosophic soft set [10] These concepts are widely applicable to different life branches, they lack the ability to handle two-dimensional problems. This motivates the definition of Q-fuzzy soft set [11,12] that served the uncertainty and two-dimensionality simultaneously. Q-NSES has the capacity to handle indeterminacy and two-dimensionality simultaneously, since it incorporates the elements of both soft expert set and Q-neutrosophic set The structure of this concept enables it to provide the opinions of experts to activate the data obtained from individuals and able to present the ideas within a two-dimensional indeterminate environment which makes it suitable to describe many real problems. The commutative and associative laws of these operations will be proposed and an application of GQ-NSES in decision-making will be illustrated
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
