Algorithms for single-valued neutrosophic decision making based on TOPSIS and clustering methods with new distance measure

Single-valued neutrosophic set (SVNS) is an important contrivance for directing the decision-making queries with unknown and indeterminant data by employing a degree of “acceptance”, “indeterminacy”, and “non-acceptance” in quantitative terms. Under this set, the objective of this paper is to propos...

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Bibliographic Details
Published inAIMS mathematics Vol. 5; no. 3; pp. 2671 - 2693
Main Authors Garg, Harish, Nancy
Format Journal Article
LanguageEnglish
Published AIMS Press 01.01.2020
Subjects
clustering algorithm
decision-making
information measure
single-valued neutrosophic set
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Summary:Single-valued neutrosophic set (SVNS) is an important contrivance for directing the decision-making queries with unknown and indeterminant data by employing a degree of “acceptance”, “indeterminacy”, and “non-acceptance” in quantitative terms. Under this set, the objective of this paper is to propose some new distance measures to find discrimination between the SVNSs. The basic axioms of the measures have been highlighted and examined their properties. Furthermore, to examine the relevance of proposed measures, an extended TOPSIS (“technique for order preference by similarity to ideal solution”) method is introduced to solve the group decision-making problems. Additionally, a new clustering technique is proposed based on the stated measures to classify the objects. The advantages, comparative analysis as well as superiority analysis is given to shows its influence over existing approaches.
ISSN:2473-6988
2473-6988
DOI:10.3934/math.2020173