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A note on ranking of L-R fuzzy numbers

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Abstract

Numerous ranking methods have been proposed and investigated so-far. Most of the ranking methods discussed only normal fuzzy numbers, but in many cases (such as risk analysis, approximate reasoning, etc.,) the normal fuzzy number is not adequate. In this paper, we introduced a new ranking method based on weighted expected values of the fuzzy numbers which can be applied for both normal and non-normal fuzzy numbers. The weighted expected interval is the nearest interval for the given fuzzy number. Furthermore, the proposed method compared with the existing methods through numerical examples.

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Acknowledgements

The authors would like to thanks to the Editor-in-Chief and anonymous referees for the various suggestions which have led to an improvement in both the quality and clarity of the paper.

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Authors and Affiliations

  1. Department of Applied Mathematics and Computational Sciences, PSG College of Technology (Autonomous), Coimbatore, Tamil Nadu, India

    C. Veeramani & M. Sumathi

  2. Department of Mathematics, Kongu Engineering College (Autonomous), Perundurai, Tamil Nadu, India

    C. Duraisamy

Authors
  1. C. Veeramani
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  2. C. Duraisamy
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  3. M. Sumathi
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Correspondence to C. Veeramani.

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Veeramani, C., Duraisamy, C. & Sumathi, M. A note on ranking of L-R fuzzy numbers. OPSEARCH 50, 282–296 (2013). https://doi.org/10.1007/s12597-012-0109-y

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