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Decision-making strategy based on Archimedean Bonferroni mean operators under complex Pythagorean fuzzy information

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Abstract

Decision-making is one of the most crucial processes to find the best optimal among the distinct attributes in an uncertain environment. However, considering more than one attribute simultaneously during the process is well handled by the Bonferroni mean operator. In this paper, we present a decision-making algorithm to solve the multi-attribute decision-making process by utilizing the features of the Archimedean Bonferroni mean operator. The advantages of the ABM are to consider the inter-relationship factors using the parameters and the operations using the t-norm and t-conorm. The uncertainty presented in the data is handled with the help of the complex Pythagorean fuzzy information. Also, we stated the more generalized aggregation operators to aggregate the different information and investigated their properties. The performance of the indicated algorithm is explained through a numerical example and compares its performance with the existing studies. The results show that our approach performs well over the current methods. A decision-maker can select a more practical alternative by varying the algorithm's parameters.

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Abbreviations

FS :

Fuzzy set

IFS :

Intuitionistic fuzzy set

PFS :

Pythagorean fuzzy set

CFS :

Complex fuzzy set

CIFS :

Complex intuitionistic fuzzy set

CPFS :

Complex Pythagorean fuzzy set

BM :

Bonferroni mean

ABM :

Archimedean Bonferroni mean

CPFABM :

Complex Pythagorean fuzzy Archimedean Bonferroni mean

CPFWABM :

Complex Pythagorean fuzzy weighted Archimedean Bonferroni mean

MADM :

Multi-attribute decision-making

TG :

Truth grade

FG :

Falsity grade

TN :

T-norm

TCN :

T-conorm

CPFNs :

Complex Pythagorean fuzzy numbers

SV :

Score value

AV :

Accuracy value

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Acknowledgements

The first author (Harish Garg) is grateful to DST-FIST grant SR/FST/MS-1/2017/13 for providing technical support.

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Authors and Affiliations

  1. School of Mathematics, Thapar Institute of Engineering and Technology (Deemed University), Patiala, 147004, Punjab, India

    Harish Garg

  2. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Yong Deng

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

    Zeeshan Ali & Tahir Mahmood

Authors
  1. Harish Garg
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  2. Yong Deng
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  3. Zeeshan Ali
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  4. Tahir Mahmood
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Corresponding authors

Correspondence to Harish Garg or Yong Deng.

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Communicated by Anibal Tavares de Azevedo.

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Garg, H., Deng, Y., Ali, Z. et al. Decision-making strategy based on Archimedean Bonferroni mean operators under complex Pythagorean fuzzy information. Comp. Appl. Math. 41, 152 (2022). https://doi.org/10.1007/s40314-022-01837-y

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  • DOI: https://doi.org/10.1007/s40314-022-01837-y

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