Version 1
: Received: 31 March 2018 / Approved: 2 April 2018 / Online: 2 April 2018 (08:47:02 CEST)
How to cite:
Pramanik, S.; Dey, P. P.; Smarandache, F. MADM Strategy Based on Some Similarity Measures in Interval Bipolar neuTrosophic Set Environment. Preprints2018, 2018040012. https://doi.org/10.20944/preprints201804.0012.v1
Pramanik, S.; Dey, P. P.; Smarandache, F. MADM Strategy Based on Some Similarity Measures in Interval Bipolar neuTrosophic Set Environment. Preprints 2018, 2018040012. https://doi.org/10.20944/preprints201804.0012.v1
Pramanik, S.; Dey, P. P.; Smarandache, F. MADM Strategy Based on Some Similarity Measures in Interval Bipolar neuTrosophic Set Environment. Preprints2018, 2018040012. https://doi.org/10.20944/preprints201804.0012.v1
APA Style
Pramanik, S., Dey, P. P., & Smarandache, F. (2018). MADM Strategy Based on Some Similarity Measures in Interval Bipolar neuTrosophic Set Environment. Preprints. https://doi.org/10.20944/preprints201804.0012.v1
Chicago/Turabian Style
Pramanik, S., Partha Pratim Dey and Florentin Smarandache. 2018 "MADM Strategy Based on Some Similarity Measures in Interval Bipolar neuTrosophic Set Environment" Preprints. https://doi.org/10.20944/preprints201804.0012.v1
Abstract
The paper investigates some similarity measures in interval bipolar neutrosophic environment for multi-attribute decision making problems. At first, we define Hamming and Euclidean distances measures between interval bipolar neutrosophic sets and establish their basic properties. We also propose two similarity measures based on the Hamming and Euclidean distance functions. Using maximum and minimum operators, we define new similarity measures and prove their basic properties. Using the proposed similarity measures, we propose a novel multi attribute decision making strategy in interval bipolar neutrosophic set environment. Lastly, we solve an illustrative example of multi attribute decision making and present comparison analysis to show the feasibility, applicability and effectiveness of the proposed strategy.
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
