HyperRough TOPSIS Method and SuperHyperRough TOPSIS Method

Authors

  • Takaaki Fujita * Independence

https://doi.org/10.48313/uda.vi.53

Abstract

Rough set theory provides a mathematical framework for approximating subsets through lower and upper bounds defined by equivalence relations, effectively capturing uncertainty in classification and data analysis. Building on these foundational ideas, extended models—such as hyper-rough sets and super-hyper-rough sets—have been proposed to represent more complex forms of uncertainty. In this paper, we introduce the HyperRough TOPSIS and SuperHyperRough TOPSIS methods and examine their underlying mathematical structures. TOPSIS is a well-established decision-making method, and the proposed HyperRough and SuperHyperRough TOPSIS approaches serve as generalized extensions of the classical Rough TOPSIS framework.

Keywords:

Rough Set, Hyperrough Set, SuperHyperRough set, TOPSIS

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Published

2025-05-31

Issue

Articles in Press

Section

Articles

How to Cite

Fujita, T. (2025). HyperRough TOPSIS Method and SuperHyperRough TOPSIS Method. Uncertainty Discourse and Applications. https://doi.org/10.48313/uda.vi.53

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