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Research Article | Open Access

Pythagorean multi-fuzzy N-soft sets: a novel hybrid model for group decision making and its applications in distance education

Fatia Fatimah1Elin Herlinawati1( ) Andriyansah2
Department of Mathematics, Faculty of Science and Technology, Universitas Terbuka, South Tangerang 15418, Indonesia
Department of Management, Faculty of Economics and Business, Universitas Terbuka, South Tangerang 15418, Indonesia
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Abstract

The rapid development of distance education has led to a pressing need for practical evaluation of learning platforms, especially in situations where decision-making involves multiple evaluators and uncertain information. To address this need, we introduce a new hybrid model called Pythagorean Multi-Fuzzy N-Soft Sets (PMFNSS). This model is designed to improve group decision-making under complex and ambiguous conditions. The proposed PMFNSS model was built by combining Pythagorean Fuzzy N-Soft Sets (PFNSS) and Multi-Fuzzy N-Soft Sets (MFNSS). First, we formally defined the concept of PMFNSS. Next, we proposed a group decision-making algorithm based on the framework. Finally, to validate its applicability, the model was used in a real-life case study on the evaluation of digital learning platforms in distance education. The results indicated that PMFNSS can serve as a multi-attribute group decision-making tool. Its application to distance education offers a systematic approach to evaluating and optimizing digital learning platforms for resource efficiency and sustainability.

CLC number: 03E72, 03E75

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AIMS Mathematics
Pages 6420-6436

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Cite this article:
Fatimah F, Herlinawati E, Andriyansah. Pythagorean multi-fuzzy N-soft sets: a novel hybrid model for group decision making and its applications in distance education. AIMS Mathematics, 2026, 11(3): 6420-6436. https://doi.org/10.3934/math.2026265

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Received: 28 September 2025
Revised: 14 January 2026
Accepted: 28 January 2026
Published: 15 March 2026
©2026 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)