Abstract
Smarandache defined a neutrosophic set to handle problems involving incompleteness, indeterminacy, and awareness of inconsistency knowledge, and have further developed it neutrosophic soft expert sets. In this paper, this concept is further expanded to generalized neutrosophic soft expert set (GNSES). We then define its basic operations of complement, union, intersection, AND, OR, and study some related properties, with supporting proofs. Subsequently, we define a GNSES-aggregation operator to construct an algorithm for a GNSES decision-making method, which allows for a more efficient decision process. Finally, we apply the algorithm to a decision-making problem, to illustrate the effectiveness and practicality of the proposed concept. A comparative analysis with existing methods is done and the result affirms the flexibility and precision of our proposed method.
Highlights
For a proper description of objects in an uncertain and ambiguous environment, indeterminate and incomplete information has to be properly handled
Intuitionistic fuzzy sets were introduced by Atanassov [1], followed by Molodtsov on soft sets [2] and neutrosophy logic [3] and neutrosophic sets [4] were introduced by Smarandache
Alhazaymeh and Hassan [21,22] have studied the concept of vague soft set, which were later extended to vague soft expert set theory [23,24], bipolar fuzzy soft expert set [25], and multi
Summary
For a proper description of objects in an uncertain and ambiguous environment, indeterminate and incomplete information has to be properly handled. Alhazaymeh and Hassan [21,22] have studied the concept of vague soft set, which were later extended to vague soft expert set theory [23,24], bipolar fuzzy soft expert set [25], and multi. This paper anticipates the neutrosophic set discussions to handle problems involving incompleteness, indeterminacy, and awareness of inconsistency of knowledge, which is further developed to neutrosophic soft expert sets. We intend to extend the discussion further, by proposing the concept of generalized neutrosophic soft expert set (GNSES) and its basic operations of complement, union, intersection, AND, and OR, along with a definition of GNSES-aggregation operator, to construct an algorithm of a GNSES decision method. We provide an application of the constructed algorithm to solve a decision-making problem
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