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Research Article | Open Access

Averaging aggregation operators under the environment of q-rung orthopair picture fuzzy soft sets and their applications in MADM problems

Sumbal Ali1( )Asad Ali1( )Ahmad Bin Azim1Ahmad ALoqaily2,3Nabil Mlaiki2
Department of Mathematics & Statistics, Hazara University, Mansehra, 21120, Pakistan
Department of Mathematics and Sciences, Prince Sultan University. Riyadh, 11586, Saudi Arabia
School of computer, Data, and Mathematical Sciences, Western Sydney University, Australia-Sydney-2150
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Abstract

q-Rung orthopair fuzzy soft set handles the uncertainties and vagueness by membership and non-membership degree with attributes, here is no information about the neutral degree so to cover this gap and get a generalized structure, we present hybrid of picture fuzzy set and q-rung orthopair fuzzy soft set and initiate the notion of q-rung orthopair picture fuzzy soft set, which is characterized by positive, neutral and negative membership degree with attributes. The main contribution of this article is to investigate the basic operations and some averaging aggregation operators like q-rung orthopair picture fuzzy soft weighted averaging operator and q-rung orthopair picture fuzzy soft order weighted averaging operator under the environment of q-rung orthopair picture fuzzy soft set. Moreover, some fundamental properties and results of these aggregation operators are studied, and based on these proposed operators we presented a stepwise algorithm for MADM by taking the problem related to medical diagnosis under the environment of q-rung orthopair picture fuzzy soft set and finally, for the superiority we presented comparison analysis of proposed operators with existing operators.

CLC number: 60L70, 68N17

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AIMS Mathematics
Pages 9027-9053

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Cite this article:
Ali S, Ali A, Azim AB, et al. Averaging aggregation operators under the environment of q-rung orthopair picture fuzzy soft sets and their applications in MADM problems. AIMS Mathematics, 2023, 8(4): 9027-9053. https://doi.org/10.3934/math.2023452

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Received: 31 October 2022
Revised: 04 February 2023
Accepted: 06 February 2023
Published: 15 April 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)