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New Ranking Approach to Solve MCDM Problems with Generalized Intuitionistic Fuzzy Information

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Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 420))

Abstract

Ranking of Generalized intuitionistic fuzzy sets (GIFSs) assume an unmistakable part, considering the fact that its applicability and appeal to mannequin with uncertainty in “Multi-criteria Decision Making” (MCDM) problems. Intention of this discussion is to inspect the more than one attribute selection issues with GIF data in which priority vectors are absolutely known. Here we lengthen “technique for order preference similarity to ideal solution (TOPSIS) method” for the generalized intuitionistic fuzzy information. Possibility degree approach are used to positioned the alternatives.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Ganesh Dutt College, Begusarai, India

    Amal Kumar Adak

  2. Lalit Narayan Mithila University, Darbhanga, India

    Nilkamal & Kaushila Nandan Srivastava

Authors
  1. Amal Kumar Adak
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  2. Nilkamal
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  3. Kaushila Nandan Srivastava
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Corresponding author

Correspondence to Amal Kumar Adak .

Editor information

Editors and Affiliations

  1. Department of Computer and Information Science, Raiganj University, Raiganj, West Bengal, India

    Laxminarayan Sahoo

  2. School of Mathematics and Statistics, Southwest University, Chongqing, China

    Tapan Senapati

  3. Iona College, Machine Intelligence Institute, New Rochelle, NY, USA

    Ronald R. Yager

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Adak, A.K., Nilkamal, Srivastava, K.N. (2023). New Ranking Approach to Solve MCDM Problems with Generalized Intuitionistic Fuzzy Information. In: Sahoo, L., Senapati, T., Yager, R.R. (eds) Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain. Studies in Fuzziness and Soft Computing, vol 420. Springer, Singapore. https://doi.org/10.1007/978-981-19-4929-6_26

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