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MADM Strategies Based on Arithmetic and Geometric Mean Operator Under Rough-Bipolar Neutrosophic Set Environment

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Transactions on Rough Sets XXIII

Part of the book series: Lecture Notes in Computer Science ((TRS,volume 13610))

Abstract

The main focus of this paper is to introduce some aggregation operators namely, Rough-Bipolar Neutrosophic Arithmetic Mean (RBNAM) operator and Rough-Bipolar Neutrosophic Geometric Mean (RBNGM) operator under Rough-Bipolar Neutrosophic Set (RBNS) environment. Besides, we present the concept of score and accuracy functions under the RBNS environment. Further, we propose two multi-attribute decision-making (MADM) strategies based on RBNAM operator and RBNGM operator respectively under the RBNS environment. Finally, we provide a real-life numerical example to validate the proposed MADM strategy.

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Authors and Affiliations

  1. Department of Mathematics, Nandalal Ghosh B.T. College, Narayanpur, 743126, West Bengal, India

    Surapati Pramanik

  2. Department of Mathematics, Tripura University, Agartala, 799022, West Tripura, India

    Suman Das, Rakhal Das & Binod Chandra Tripathy

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  1. Surapati Pramanik
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  2. Suman Das
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  3. Rakhal Das
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  4. Binod Chandra Tripathy
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All the authors have equal contribution for the preparation of this article.

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Correspondence to Surapati Pramanik .

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Editors and Affiliations

  1. University of Manitoba, Winnipeg, MB, Canada

    James F. Peters

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Andrzej Skowron

  3. Tripura University, Agartala, India

    Rabi Nanda Bhaumik

  4. University of Winnipeg, Winnipeg, MB, Canada

    Sheela Ramanna

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Pramanik, S., Das, S., Das, R., Tripathy, B.C. (2022). MADM Strategies Based on Arithmetic and Geometric Mean Operator Under Rough-Bipolar Neutrosophic Set Environment. In: Peters, J.F., Skowron, A., Bhaumik, R.N., Ramanna, S. (eds) Transactions on Rough Sets XXIII. Lecture Notes in Computer Science(), vol 13610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-66544-2_5

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  • DOI: https://doi.org/10.1007/978-3-662-66544-2_5

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