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A multi-criteria group decision-making approach based on revised distance measures under dual hesitant fuzzy setting with unknown weight information

  • Fuzzy systems and their mathematics
  • Published:
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Abstract

This study aims to revise the existing distance and similarity measures of the dual hesitant fuzzy set (DHFS) context in order to remove their shortcomings. The study first reveals the limitations of the existing distance measures of DHFSs through some counterexamples. Keeping in mind the indicated limitations of the existing ones, we revise them and show how the revised measures are important by applying them to the pattern recognition problem. Further, the statistical variance (SV) method is extended to the DHFS context for criteria weight determination. After that, an approach is made based on revised distance measures for ranking alternatives in multi-criteria group decision making (MCGDM). In the end, a real-world example regarding the evaluation of the quality of movies is presented to elaborate on the practicality and superiority of the developed approach.

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Authors and Affiliations

  1. Department of Mathematics, Quaid-i-Azam University, Islamabad, 45320, Pakistan

    Jawad Ali & Zia Bashir

  2. Department of Mathematics, University of Management and Technology, Lahore, 54770, Pakistan

    Tabasam Rashid

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  1. Jawad Ali
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  2. Zia Bashir
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  3. Tabasam Rashid
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Correspondence to Tabasam Rashid.

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Ali, J., Bashir, Z. & Rashid, T. A multi-criteria group decision-making approach based on revised distance measures under dual hesitant fuzzy setting with unknown weight information. Soft Comput 26, 8387–8401 (2022). https://doi.org/10.1007/s00500-022-07208-3

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