Optimal Parameter Identification in Soft Set Frameworks: A Decision Support Model

Resumo

This paper addresses the critical issue of decision-making under uncertainty, with a particular focus on soft set theory. Soft sets offer robust mathematical tools for handling uncertainty, making them highly suitable for solving real-world problems characterized by incomplete or imprecise information. In this study, a novel algorithm is proposed to handle specific types of uncertain situations, effectively targeting a distinct class of uncertainty-related problems. The research also highlights the significance of collaborative evaluation processes in group decision-making, emphasizing the role of collective input in identifying optimal solutions in uncertain environments.

The key contribution of this study lies in enhancing decision-making processes under uncertainty, with broad applicability to complex, real-life scenarios influenced by ambiguous or incomplete data. The findings are expected to benefit both researchers and practitioners dealing with uncertainty-driven challenges, providing practical and applicable solutions. Moreover, this study serves as a foundation for future research and innovation in the field, offering valuable insights into the development of advanced decision-making frameworks under uncertainty.

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Biografia do Autor

Naime Demirtas, Mersin University

Associate Prof. Dr. Naime Demirtas, Department of Mathematics, Mersin University.

Orhan Dalkilic, Bingol University,Science Faculty, Department of Mathematics, Bingol, Turkiye.

Bingol University,Science Faculty, Department of Mathematics, Bingol, Turkiye.

Referências

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Publicado
2025-08-11
Seção
Artigos