An MADM-based fuzzy parameterized framework for solar panels evaluation in a fuzzy hypersoft expert set environment

Muhammad Ihsan; Muhammad Saeed; Atiqe Ur Rahman; Hüseyin Kamacı; Nehad Ali Shah; Wajaree Weera; Muhammad Ihsan; Muhammad Saeed; Atiqe Ur Rahman; Hüseyin Kamacı; Nehad Ali Shah; Wajaree Weera

doi:10.3934/math.2023175

AIMS Mathematics

2023, Volume 8, Issue 2: 3403-3427. doi: 10.3934/math.2023175

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Research article

An MADM-based fuzzy parameterized framework for solar panels evaluation in a fuzzy hypersoft expert set environment

1.
Department of Mathematics, University of Management and Technology, Lahore 54000, Pakistan
2.
Department of Mathematics, Yozgat Bozok University, Yozgat 66900, Turkey
3.
Department of Mechanical Engineering, Sejong University, Seoul 05006, South Korea
4.
Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand
^† These authors contributed equally to this work and are co-first authors

Received: 26 August 2022 Revised: 25 September 2022 Accepted: 10 October 2022 Published: 21 November 2022
MSC : 03B52, 03E72, 03E75

The selection of parameters plays a vital role in the multi-attribute decision-making process. In some situations, it is observed that the nature of parameters is ambiguous and a multi-decisive opinion is necessary for managing such parametric uncertainty. In the literature, there is no suitable model that can cope with such situations. This study was purposed to develop a novel context called the fuzzy parameterized fuzzy hypersoft expert set (FPFHSE-set), which is capable of managing the uncertain nature of parameters and the multi-decisive opinion of experts collectively in one model. In this way, the proposed model may be described as the generalization of the existing model fuzzy parameterized fuzzy soft expert set (FPFSE-set). Theoretic, axiomatic and algorithmic approaches have been employed for the characterization of the basic notions of the FPFHSE-set. In order to handle multi-attribute decision-making, two algorithms are proposed and then validated by applying them to some real-world scenarios in the FPFHSE-set environment. The merits and superiority of the new algorithms are presented by comparing them with some existing fuzzy decision-making models. According to the proposed FPFHSE-set-based decision-making approaches, the experts have more freedom in specifying their preferences and thoughts according to their expertise, and they can process new types of data. Therefore, this paper presents a state-of-the-art improvement that provides a holistic view to understand and handle the multi-attribute decision-making issues focused on the objective of classifying alternatives according to multiple attributes by multiple experts.
- fuzzy set,
- soft set,
- hypersoft set,
- hypersoft expert set,
- fuzzy parameterized fuzzy hypersoft expert set,
- decision making
Citation: Muhammad Ihsan, Muhammad Saeed, Atiqe Ur Rahman, Hüseyin Kamacı, Nehad Ali Shah, Wajaree Weera. An MADM-based fuzzy parameterized framework for solar panels evaluation in a fuzzy hypersoft expert set environment[J]. AIMS Mathematics, 2023, 8(2): 3403-3427. doi: 10.3934/math.2023175

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Abstract

The selection of parameters plays a vital role in the multi-attribute decision-making process. In some situations, it is observed that the nature of parameters is ambiguous and a multi-decisive opinion is necessary for managing such parametric uncertainty. In the literature, there is no suitable model that can cope with such situations. This study was purposed to develop a novel context called the fuzzy parameterized fuzzy hypersoft expert set (FPFHSE-set), which is capable of managing the uncertain nature of parameters and the multi-decisive opinion of experts collectively in one model. In this way, the proposed model may be described as the generalization of the existing model fuzzy parameterized fuzzy soft expert set (FPFSE-set). Theoretic, axiomatic and algorithmic approaches have been employed for the characterization of the basic notions of the FPFHSE-set. In order to handle multi-attribute decision-making, two algorithms are proposed and then validated by applying them to some real-world scenarios in the FPFHSE-set environment. The merits and superiority of the new algorithms are presented by comparing them with some existing fuzzy decision-making models. According to the proposed FPFHSE-set-based decision-making approaches, the experts have more freedom in specifying their preferences and thoughts according to their expertise, and they can process new types of data. Therefore, this paper presents a state-of-the-art improvement that provides a holistic view to understand and handle the multi-attribute decision-making issues focused on the objective of classifying alternatives according to multiple attributes by multiple experts.

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