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A novel similarity measure based on new accuracy function on interval-valued intuitionistic fuzzy number and its application to multicriteria decision-making problem

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Abstract

Interval-valued intuitionistic fuzzy numbers (IVIFNs) are perfect to even more naturally model real-life issues and can be applied to several area like cluster analysis, decision-making, image processing, medical diagnosis, pattern recognition, etc. In particular, the similarity measures defined on IVIFNs take an important role in these fields effectively. Most of the researchers have tried to find a unique method (similarity measure) that may be appropriate for many problems. Apparently, there are several disadvantages to every one of them. First, in this paper, by using general accuracy function defined on IVIFNs, we define a new distance measure and hence a similarity measure for the class of IVIFNs. Second, some properties of these proposed measures are discussed by numerical problems. Third, the drawbacks of existing similarity measures are discussed and compared with the proposed similarity measure in various cases using numerical examples. Finally, the applicability of the proposed method for solving the problem of multicriteria decision making (MCDM) using TOPSIS technique is shown.

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Acknowledgements

The authors wish to express their thanks to the anonymous referees and editors for their valuable comments which improved the quality of the paper.

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Authors and Affiliations

  1. Department of Mathematics, St. Joseph’s College (Autonomous) (Affiliated to Bharathidasan University), Tiruchirappalli, Tamil Nadu, India

    P. Vishnukumar & Geetha Sivaraman

  2. Department of Mathematics, K. Ramakrishnan College of Engineering (Autonomous), Tiruchirappalli, Tamil Nadu, India

    M. Edwin Antony Raj

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  1. P. Vishnukumar
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  2. M. Edwin Antony Raj
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  3. Geetha Sivaraman
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Correspondence to P. Vishnukumar.

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Vishnukumar, P., Edwin Antony Raj, M. & Sivaraman, G. A novel similarity measure based on new accuracy function on interval-valued intuitionistic fuzzy number and its application to multicriteria decision-making problem. Neural Comput & Applic 36, 5183–5195 (2024). https://doi.org/10.1007/s00521-023-09313-2

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