A general framework for multi-granulation rough decision-making method under q-rung dual hesitant fuzzy environment

Abstract

In the realistic decision-making (DM) process, the DM results were provided by multiple DM experts, which are more accurate than those based on one DM expert. Therefore, the multi-granulation rough set (MGRS) model is more accurate in DM problems. It is imperative to apply the idea of multi-granulation to the complex fuzzy uncertain information. By combining q-rung dual hesitant fuzzy sets (q-DHFSs) with multi-granulation rough sets (MGRSs) over two universes, we propose a q-rung dual hesitant fuzzy multi-granulation rough set (q-RDHFMGRS) over two universes, and prove some of their basic properties. Then, based on this model, we propose a new multi-attribute DM algorithm. Finally, we validate the practicability and validity of the algorithm through an example of medical diagnosis.

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Acknowledgements

The authors would like to thank the Editor in Chief and the anonymous reviewers for providing very helpful comments and suggestions which improved the paper.

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Correspondence to Yabin Shao.

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This work was supported by the National Natural Science Foundation of China (Grant Nos. 61763044, 61876201 and 11901265)

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Shao, Y., Qi, X. & Gong, Z. A general framework for multi-granulation rough decision-making method under q-rung dual hesitant fuzzy environment. Artif Intell Rev 53, 4903–4933 (2020). https://doi.org/10.1007/s10462-020-09810-z

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Keywords

  • q-rung dual hesitant fuzzy set
  • Multi-granulation rough set
  • Decision rule
  • Medical diagnosis