Multi-attribute Decision Making based on Rough Neutrosophic Variational Coefficient Similarity Measure

Authors

  • Kalyan Mondal Department of Mathematics, Jadavpur University, West Bengal, India
  • Surapati Pramanik Department of Mathematics, Nandalal Ghosh B.T. College, Panpur, PO-Narayanpur, and District: North 24 Parganas, Pin Code: 743126, West Bengal, India.
  • Florentin Smarandache University of New Mexico. Mathematics & Science Department, 705 Gurley Ave., Gallup, NM 87301, USA.

Keywords:

Neutrosophic set, Rough neutrosophic set; Rough variation coefficient similarity measure; Decision making.

Abstract

Abstract: The purpose of this study is to propose new similarity measures namely rough variational coefficient similarity measure under the rough neutrosophic environment. The weighted rough variational coefficient similarity measure has been also defined. The weighted rough variational coefficient similarity measures between the rough ideal alternative and each alternative are calculated to find the best alternative. The ranking order of all the alternatives can be determined by using the numerical values of similarity measures. Finally, an illustrative example has been provided to show the effectiveness and validity of the proposed approach. Comparisons of decision results of existing rough similarity measures have been provided.

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Published

2016-12-15

Issue

Section

SI#1,2024: Neutrosophical Advancements And Their Impact on Research

How to Cite

Mondal, K. ., Pramanik, . S. ., & Smarandache, . F. . (2016). Multi-attribute Decision Making based on Rough Neutrosophic Variational Coefficient Similarity Measure . Neutrosophic Sets and Systems, 13, 3-17. https://fs.unm.edu/nss8/index.php/111/article/view/498

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