Sustainable thermal power equipment supplier selection by Einstein prioritized linear Diophantine fuzzy aggregation operators

Hafiz Muhammad Athar Farid; Muhammad Riaz; Muhammad Jabir Khan; Poom Kumam; Kanokwan Sitthithakerngkiet; Hafiz Muhammad Athar Farid; Muhammad Riaz; Muhammad Jabir Khan; Poom Kumam; Kanokwan Sitthithakerngkiet

doi:10.3934/math.2022627

AIMS Mathematics

2022, Volume 7, Issue 6: 11201-11242. doi: 10.3934/math.2022627

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Research article

Sustainable thermal power equipment supplier selection by Einstein prioritized linear Diophantine fuzzy aggregation operators

1.
Department of Mathematics, University of the Punjab, Lahore, Pakistan
2.
KMUTT Fixed Point Research Laboratory, Science Laboratory Building, Department of Mathematics, Faculty of Science, King Mongkut's University of Technology Thonburi (KMUTT), 126 Pracha-Uthit Road, Bang Mod, Thung Khru, Bangkok 10140, Thailand
3.
Center of Excellence in Theoretical and Computational Science (TaCS-CoE), SCL 802 Fixed Point Laboratory, Science Laboratory Building, KMUTT, 126 Pracha-Uthit Road, Bang Mod, Thung Khru, Bangkok 10140, Thailand
4.
Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 40402, Taiwan
5.
Intelligent and Nonlinear Dynamic Innovations Research Center, Department of Mathematics, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok (KMUTNB), 1518, Wongsawang, Bangsue, Bangkok 10800, Thailand

Received: 09 January 2022 Revised: 13 March 2022 Accepted: 21 March 2022 Published: 11 April 2022
MSC : 03E72, 94D05, 90B50

Clean energy potential can be used on a large scale in order to achieve cost competitiveness and market effectiveness. This paper offers sufficient information to choose renewable technology for improving the living conditions of the local community while meeting energy requirements by employing the notion of q-rung orthopair fuzzy numbers (q-ROFNs). In real-world situations, a q-ROFN is exceptionally useful for representing ambiguous/vague data. A multi-criteria decision-making (MCDM) is proposed in which the parameters have a prioritization relationship and the idea of a priority degree is employed. The aggregation operators (AOs) are formed by awarding non-negative real numbers known as priority degrees among strict priority levels. Consequently, some prioritized operators with q-ROFNs are proposed named as "q-rung orthopair fuzzy prioritized averaging ($\text{q-ROFPA} _d $) operator with priority degrees and q-rung orthopair fuzzy prioritized geometric ($\text{q-ROFPG} _d $) operator with priority degrees". The results of the proposed approach are compared with several other related studies. The comparative analysis results indicate that the proposed approach is valid and accurate which provides feasible results. The characteristics of the existing method are often compared to other current methods, emphasizing the superiority of the presented work over currently used operators. Additionally, the effect of priority degrees is analyzed for information fusion and feasible ranking of objects.
- prioritized aggregation operators,
- priority degrees,
- sustainable energy,
- Gwadar,
- q-rung orthopair fuzzy numbers and MCDM
Citation: Hafiz Muhammad Athar Farid, Muhammad Riaz, Muhammad Jabir Khan, Poom Kumam, Kanokwan Sitthithakerngkiet. Sustainable thermal power equipment supplier selection by Einstein prioritized linear Diophantine fuzzy aggregation operators[J]. AIMS Mathematics, 2022, 7(6): 11201-11242. doi: 10.3934/math.2022627

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Abstract

Clean energy potential can be used on a large scale in order to achieve cost competitiveness and market effectiveness. This paper offers sufficient information to choose renewable technology for improving the living conditions of the local community while meeting energy requirements by employing the notion of q-rung orthopair fuzzy numbers (q-ROFNs). In real-world situations, a q-ROFN is exceptionally useful for representing ambiguous/vague data. A multi-criteria decision-making (MCDM) is proposed in which the parameters have a prioritization relationship and the idea of a priority degree is employed. The aggregation operators (AOs) are formed by awarding non-negative real numbers known as priority degrees among strict priority levels. Consequently, some prioritized operators with q-ROFNs are proposed named as "q-rung orthopair fuzzy prioritized averaging ($\text{q-ROFPA} _d $) operator with priority degrees and q-rung orthopair fuzzy prioritized geometric ($\text{q-ROFPG} _d $) operator with priority degrees". The results of the proposed approach are compared with several other related studies. The comparative analysis results indicate that the proposed approach is valid and accurate which provides feasible results. The characteristics of the existing method are often compared to other current methods, emphasizing the superiority of the presented work over currently used operators. Additionally, the effect of priority degrees is analyzed for information fusion and feasible ranking of objects.

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