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Research Article | Open Access

Obesity treatment applying effective fuzzy soft multiset-based decision-making process

Department of Management Information Systems, College of Business Administration in Hawtat Bani Tamim, Prince Sattam Bin Abdulaziz University, Saudi Arabia
Department of Mathematics, Faculty of Education, Ain Shams University, Cairo 11341, Egypt
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Abstract

Nowadays, obesity is recognized as a worldwide epidemic that has become a major cause of death and comorbidities. Recommending appropriate treatment is critical in the global health environment. For obesity treatment to be effective, the person must be able to follow a specific diet that meets his needs so that he can follow it for a long time or forever to maintain fitness. This research aims to determine the best diet among the trusted diets for every person based on his needs and circumstances. This occurs when applying a decision-making technique based on the effective fuzzy soft multiset concept. For this purpose, the definition of the effective fuzzy soft multiset as well as its types, operations, and properties are introduced. Furthermore, a decision-making method is proposed based on the effective fuzzy soft multiset environment. Using matrices operations, one can easily apply the decision-making process based on this new extension of sets to choose the optimal diet for everyone. Finally, an extensive comparative analysis of the previous methods is undertaken and also summarized in a chart to attract focus on the benefits of the suggested algorithm and to demonstrate how they differ from the current one.

CLC number: 03E72, 03E05, 92C50

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AIMS Mathematics
Pages 26765-26798

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Cite this article:
Sakr HH. Obesity treatment applying effective fuzzy soft multiset-based decision-making process. AIMS Mathematics, 2024, 9(10): 26765-26798. https://doi.org/10.3934/math.20241302

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Received: 23 July 2024
Revised: 28 August 2024
Accepted: 04 September 2024
Published: 15 October 2024
©2024 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)