Exploring Symmetry in Industrial Decision-Making: A New Framework Based on Cubic Type-2 Fuzzy Soft Sets

Abstract

Industry 4.0 supply chains, characterized by dynamic environments, uncertainty, and intricate interdependencies, necessitate robust decision-making tools. While existing models have made strides in addressing these complexities, they often struggle to effectively handle the high degree of uncertainty inherent in such systems. To bridge this gap, this research introduces a novel framework grounded in the axioms of Cubic Type-2 Fuzzy Soft Sets (CT2FSSs). By leveraging the enhanced flexibility and uncertainty-handling capabilities of CT2FSSs, our proposed framework empowers decision-makers to navigate complexities, optimize supply chain processes, and mitigate risks while maintaining symmetry in decision-making. Through rigorous theoretical analysis and practical applications, this study not only advances fuzzy set theory but also demonstrates its efficacy in the context of Industry 4.0. The unique contribution of this research lies in the development of a CT2FSS-based framework that offers superior adaptability to uncertain and complex environments, thereby enhancing the resilience and performance of supply chains in symmetrical scenarios.

Keywords

• cubic type-2 fuzzy soft sets
• decision-making
• supply chains
• optimization
• symmetry