A Complementary Dual of Single-Valued Neutrosophic Entropy with Application to MAGDM

A single-valued neutrosophic set (SVNS) is a subcategory of neutrosophic set that is used to represent uncertainty and fuzziness in three tiers, namely truthfulness, indeterminacy, and falsity. The measure of entropy of a SVNS plays an important role to determine the ambiguity in a variety of situations. The knowledge measure is a dual form of entropy and is helpful in certain counterintuitive situations. In this paper, we introduce a knowledge measure for the SVNS and contrast the same with existing measures. The comparative study reveals that the proposed knowledge measure is more effective in modeling the structured linguistic variables. We provide the relations of the proposed knowledge measure with single valued neutrosophic similarity and distance measures. We also investigate the application of the proposed measure in multi-attribute group decision making (MAGDM). The proposed MAGDM model is helpful when the decision makers in the group have varied background and the hiring organization is unable to assign the level of importance or weight to a decision-maker.

Automated summary

This paper introduces a knowledge measure for single-valued neutrosophic sets (SVNS), compares it with existing measures, and reveals that the proposed knowledge measure is more effective in modeling structured linguistic variables. The study also investigates the application of the proposed measure in multi-attribute group decision making (MAGDM).