Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Multi-criteria decision making method based on improved cosine similarity measure with interval neutrosophic sets

Multi-criteria decision making method based on improved cosine similarity measure with interval... The fuzziness and complexity of evaluation information are common phenomenon in practical decision-making problem, interval neutrosophic sets (INSs) is a power tool to deal with ambiguous information. Similarity measure plays an important role in judging the degree between ideal and each alternative in decision-making process, the purpose of this paper is to establish a multi-criteria decision-making method based on similarity measure under INSs.Design/methodology/approachBased on an extension of existing cosine similarity, this paper first introduces an improved cosine similarity measure between interval neutosophic numbers, which considers the degrees of the truth membership, the indeterminacy membership and the falsity membership of the evaluation values. And then a multi-criteria decision-making method is established based on the improved cosine similarity measure, in which the ordered weighted averaging (OWA) is adopted to aggregate the neutrosophic information related to each alternative. Finally, an example on supplier selection is given to illustrate the feasibility and practicality of the presented decision-making method.FindingsIn the whole process of research and practice, it was realized that the application field of the proposed similarity measure theory still should be expanded, and the development of interval number theory is one of further research direction.Originality/valueThe main contributions of this paper are as follows: this study presents an improved cosine similarity measure under INSs, in which the weights of the three independent components of an interval number are taken into account; OWA are adopted to aggregate the neutrosophic information related to each alternative; and a multi-criteria decision-making method using the proposed similarity is developed under INSs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Computing and Cybernetics Emerald Publishing

Multi-criteria decision making method based on improved cosine similarity measure with interval neutrosophic sets

Loading next page...
 
/lp/emerald-publishing/multi-criteria-decision-making-method-based-on-improved-cosine-SjR00kd1bK

References (31)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1756-378X
DOI
10.1108/ijicc-05-2019-0047
Publisher site
See Article on Publisher Site

Abstract

The fuzziness and complexity of evaluation information are common phenomenon in practical decision-making problem, interval neutrosophic sets (INSs) is a power tool to deal with ambiguous information. Similarity measure plays an important role in judging the degree between ideal and each alternative in decision-making process, the purpose of this paper is to establish a multi-criteria decision-making method based on similarity measure under INSs.Design/methodology/approachBased on an extension of existing cosine similarity, this paper first introduces an improved cosine similarity measure between interval neutosophic numbers, which considers the degrees of the truth membership, the indeterminacy membership and the falsity membership of the evaluation values. And then a multi-criteria decision-making method is established based on the improved cosine similarity measure, in which the ordered weighted averaging (OWA) is adopted to aggregate the neutrosophic information related to each alternative. Finally, an example on supplier selection is given to illustrate the feasibility and practicality of the presented decision-making method.FindingsIn the whole process of research and practice, it was realized that the application field of the proposed similarity measure theory still should be expanded, and the development of interval number theory is one of further research direction.Originality/valueThe main contributions of this paper are as follows: this study presents an improved cosine similarity measure under INSs, in which the weights of the three independent components of an interval number are taken into account; OWA are adopted to aggregate the neutrosophic information related to each alternative; and a multi-criteria decision-making method using the proposed similarity is developed under INSs.

Journal

International Journal of Intelligent Computing and CyberneticsEmerald Publishing

Published: Aug 16, 2019

Keywords: Multi-criteria decision making; Supplier selection; Improved cosine similarity measure; Interval neutrosophic set

There are no references for this article.