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Some Generalized Intuitionistic Fuzzy Einstein Hybrid Aggregation Operators and Their Application to Multiple Attribute Group Decision Making

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Abstract

The objective of the present work is divided into threefold. Firstly, we developed intuitionistic fuzzy Einstein hybrid averaging (IFEHA) aggregation operator and intuitionistic fuzzy Einstein hybrid geometric (IFEHG) aggregation operator along with their desirable properties. Secondly, we introduced two generalized aggregation operators along with their desirable properties, namely generalized intuitionistic fuzzy Einstein hybrid averaging (GIFEHA) aggregation operator and generalized intuitionistic fuzzy Einstein hybrid geometric (GIFEHG) aggregation operator. The main advantage of using the proposed methods is that these operators and methods give a more complete view of the problem to the decision makers. These methods provide more general, more accurate and precise results as compared to the existing methods. Therefore, these methods play a vital role in real-world problems. Finally the proposed operators have been applied to decision-making problems to show the validity, practicality and effectiveness of the new approach.

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Authors and Affiliations

  1. Department of Mathematics, Hazara University, Mansehra, KPK, Pakistan

    Khaista Rahman

  2. Department of Mathematics, Abdul Wali Khan University, Mardan, KPK, Pakistan

    Saleem Abdullah

  3. Department of Mathematics and Statistics, Riphah International University, Islamabad, Pakistan

    Muhammad Jamil & Muhammad Yaqub Khan

Authors
  1. Khaista Rahman
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  2. Saleem Abdullah
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  3. Muhammad Jamil
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  4. Muhammad Yaqub Khan
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Correspondence to Khaista Rahman.

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Rahman, K., Abdullah, S., Jamil, M. et al. Some Generalized Intuitionistic Fuzzy Einstein Hybrid Aggregation Operators and Their Application to Multiple Attribute Group Decision Making. Int. J. Fuzzy Syst. 20, 1567–1575 (2018). https://doi.org/10.1007/s40815-018-0452-0

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  • DOI: https://doi.org/10.1007/s40815-018-0452-0

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