General Science and Philosophy


Distance and Similarity Measures for Multiple Attribute Decision Making with Single-Valued Neutrosophic Hesitant Fuzzy Information

Authors: Ridvan Şahin, Peide Liu

With respect to a combination of hesitant sets, and single-valued neutrosophic sets which are a special case of neutrosophic sets, the single valued neutrosophic hesitant sets (SVNHFS) have been proposed as a new theory set that allows the truth-membership degree, indeterminacy membership degree and falsity-membership degree including a collection of crisp values between zero and one, respectively. There is no consensus on the best way to determine the order of a sequence of singlevalued neutrosophic hesitant fuzzy elements. In this paper, we first develop an axiomatic system of distance and similarity measures between single-valued neutrosophic hesitant fuzzy sets and also propose a class of distance and similarity measures based on three basic forms such that the geometric distance model, the set-theoretic approach, and the matching functions. Then we utilize the distance measure between each alternative and ideal alternative to establish a multiple attribute decision making method under single-valued neutrosophic hesitant fuzzy environment. Finally, a numerical example of investment alternatives is provided to show the effectiveness and usefulness of the proposed approach. The advantages of the proposed distance measure over existing measures have been discussed.

Comments: 20 Pages.

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Submission history

[v1] 2016-12-07 10:12:17

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