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Group Decision-Making Framework with Generalized Orthopair Fuzzy 2-Tuple Linguistic Information

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q-Rung Orthopair Fuzzy Sets

Abstract

Many decision-making problems in real-life scenarios depend on how to deal with uncertainty, which is typically a big challenge for decision-makers (DMs). Mathematical models are not common, but where the complexity is not usually probabilistic, various models emerged along with fuzzy logic and linguistic fuzzy approach. In the linguistic environment, multiple attribute group decision-making (MAGDM) is an essential part of modern decision-making science, and information aggregation operators play a crucial role in solving MAGDM problems. The notion of generalized orthopair fuzzy sets (GOFSs) (also known as q-rung orthopair fuzzy sets) serves as an extension of intuitionistic fuzzy sets \((q=1)\) and Pythagorean fuzzy sets \((q=2)\). The generalized orthopair fuzzy 2-tuple linguistic (GOFTL) set provides a better way to deal with uncertain and imprecise information in decision-making. The Maclaurin symmetric mean (MSM) aggregation operator is a useful tool to model the interrelationship between multi-input arguments. In this chapter, we generalize the traditional MSM to aggregate GOFTL information. Firstly, the GOFTL Maclaurin symmetric mean (GOFTLMSM) and the GOFTL weighted Maclaurin symmetric mean (GOFTLWMSM) operators are proposed along with desirable properties and some special cases. Furthermore, the GOFTL dual Maclaurin symmetric mean (GOFTLDMSM) and GOFTL weighted dual Maclaurin symmetric mean (GOFTLWDMSM) operators with some properties and cases are presented. An efficient approach is developed to tackle the MAGDM problems within the GOFTL framework based on the GOFTLWMSM and GOFTLWDMSM operators. Finally, a numerical illustration regarding the selection of the most preferable supplier(s) in enterprise framework group (EFG) of companies is given to demonstrate the application of the proposed approach and exhibit its viability.

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Acknowledgements

The authors are highly grateful to the anonymous referees for their valuable comments and suggestions. This work was partially supported by the National Natural Science Foundation of China [Grant Number 11301415], the Shaanxi Provincial Key Research and Development Program [Grant Number 2021SF-480], and the Natural Science Basic Research Plan in Shaanxi Province of China [Grant Number 2018JM1054].

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Authors and Affiliations

  1. Department of Mathematics, Division of Science and Technology, University of Education, Lahore, Pakistan

    Sumera Naz & Abid Mahboob

  2. Department of Mathematics, University of the Punjab, New Campus, Lahore, 54590, Pakistan

    Muhammad Akram

  3. Department of Applied Mathematics, School of Science, Xi’an University of Posts and Telecommunications, Xi’an, 710121, China

    Feng Feng

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  1. Sumera Naz
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  2. Muhammad Akram
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  3. Feng Feng
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  4. Abid Mahboob
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Correspondence to Feng Feng .

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Editors and Affiliations

  1. Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Harish Garg

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Naz, S., Akram, M., Feng, F., Mahboob, A. (2022). Group Decision-Making Framework with Generalized Orthopair Fuzzy 2-Tuple Linguistic Information. In: Garg, H. (eds) q-Rung Orthopair Fuzzy Sets. Springer, Singapore. https://doi.org/10.1007/978-981-19-1449-2_10

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