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Fuzzy multi-granulation decision-theoretic rough sets based on fuzzy preference relation

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Abstract

Preference analysis is a class of important issues in multi-criteria decision making. The rough set theory is a powerful approach to handle preference analysis. In order to solve the multi-criteria preference analysis, this work improves the fuzzy multi-granulation decision-theoretic rough set model with additive consistent fuzzy preference relation, and it is used to analyze data from different sources, i.e., multi-source (fuzzy) information system. More specifically, we introduce the models of optimistic and pessimistic fuzzy preference relation multi-granulation decision-theoretic rough sets. Then, their principal structure, basic properties and several kinds of uncertainty measure methods are investigated as well. An example is employed to illustrate the effectiveness of the proposed models, and comparisons are also offered according to different measures of our models and existing models.

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Acknowledgements

The authors would like to thank the Associate Editor and reviewers for their thoughtful comments and valuable suggestions.

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Authors and Affiliations

  1. Bhalukdungri Jr. High School, Raigara, Purulia, West Bengal, 723153, India

    Prasenjit Mandal

  2. Department of Pure and Applied Mathematics, Guru Ghasidas University, Bilaspur, Chhattisgarh, India

    A. S. Ranadive

Authors
  1. Prasenjit Mandal
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  2. A. S. Ranadive
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Correspondence to Prasenjit Mandal.

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Mandal, P., Ranadive, A.S. Fuzzy multi-granulation decision-theoretic rough sets based on fuzzy preference relation. Soft Comput 23, 85–99 (2019). https://doi.org/10.1007/s00500-018-3411-7

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  • DOI: https://doi.org/10.1007/s00500-018-3411-7

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