Application of Neutrosophic Sets in Multi Attribute Decision Making Article Swipe

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R. Ramesh ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.52783/cana.v32.4545

The selection of an optimal hospital for healthcare services is a complex decision-making problem due to the involvement of multiple, often conflicting, criteria such as quality of care, infrastructure, staff expertise, cost, and patient satisfaction. This paper presents an innovative approach for hospital selection using a hybrid decision-making framework combining neutrosophic sets, entropy weight, and the Multi-Attribute Decision-Making (MADM) method. Neutrosophic sets are employed to handle the inherent uncertainty and indeterminacy in hospital evaluation criteria, allowing for more flexible and accurate representation of data that may not be fully precise or certain. The entropy weight method is applied to objectively determine the significance of each evaluation criterion, ensuring that the decision process is not biased by subjective judgments. Finally, the MADM technique integrates the weighted criteria into a comprehensive decision model to rank hospitals based on their overall performance. The proposed model is tested with a real-world dataset of hospitals, demonstrating its effectiveness in selecting the most suitable healthcare facility while considering diverse factors. The results highlight the potential of combining neutrosophic sets with advanced decision-making techniques for improving decision accuracy and reliability in complex healthcare decisions.

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Type: article
Language: en
Landing Page: https://doi.org/10.52783/cana.v32.4545
PDF: https://internationalpubls.com/index.php/cana/article/download/4545/2535
OA Status: diamond
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DOI: https://doi.org/10.52783/cana.v32.4545

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Title: Application of Neutrosophic Sets in Multi Attribute Decision Making

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Language: en

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Publication year: 2025

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Publication date: 2025-03-26

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Authors: R. Ramesh

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Landing page: https://doi.org/10.52783/cana.v32.4545

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PDF URL: https://internationalpubls.com/index.php/cana/article/download/4545/2535

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Concepts: Computer science, Artificial intelligence

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