Abstract
We propose the theory of possibility intuitionistic fuzzy soft expert theory and define some related concepts pertaining to this notion as well as the basic operations on this concept, namely, the complement, union, intersection, AND, and OR. The basic properties and relevant laws pertaining to this concept such as De Morgan’s laws are proved. Lastly, a generalized algorithm is introduced and applied to the concept of possibility intuitionistic fuzzy soft expert sets in hypothetical decision making problem.
Highlights
Most real-life problems involve data with a high level of uncertainty and imprecision
intuitionistic fuzzy sets (IFS) are commonly thought to be similar to the notion of interval-valued fuzzy sets (IVFS) and bipolar-valued fuzzy sets (BVFS)
We introduce some basic operations on possibility intuitionistic fuzzy soft expert sets (PIFSES), namely, the complement, AND, OR, union, and intersection of PIFSES, and proceed to study some of the properties related to these operations
Summary
Most real-life problems involve data with a high level of uncertainty and imprecision. Among the significant milestones in the development of the theory of soft sets and its generalizations is the introduction of the possibility value which indicates the degree of possibility of belongingness of the elements in the universal set (in addition to the degree of membership (and nonmembership) of each element) as well as the element of expert sets which enables the users to know the opinion of all the experts in one model without the need for any operations These new aspects have further improved the theory of soft sets and made it better suited to be used in solving decision making problems, especially when used with the more accurate generalizations of soft sets such as fuzzy soft sets and intuitionistic fuzzy soft sets.
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