ArticleScientific reports2026
The extended TODIM method under q-rung orthopair fuzzy environment and its application to multi-path parallel transmission in mobile networks.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Decision-making for engineering systems like multi-path parallel transmission is plagued by ambiguous and asymmetric information. While q-rung orthopair fuzzy sets offer expressive power, their decision-making frameworks face three intertwined gaps: (1) existing ranking methods yield unstable results under varying parameter q; (2) conventional distance measures fail to preserve higher-order structural information; (3) the prospect theory-based TODIM method, crucial for modeling risk-prone decisions, remains underdeveloped in q-rung orthopair fuzzy environments. To bridge these gaps, this paper introduces an integrated TODIM extension for q-rung orthopair fuzzy information. The core innovations are threefold. We first develop a geometric visualization-based ranking method that maps q-rung orthopair fuzzy numbers onto a coordinate plane and uses arc-length aggregation to integrate membership, non-membership, and hesitation degrees. This method inherently enhances interpretability and ranking stability against q-value fluctuations. Second, we propose a novel higher-order distance measure specifically designed to capture the nuanced structural information of q-rung orthopair fuzzy numbers, ensuring higher fidelity in difference quantification. Third, we seamlessly embed these enhanced components into the classical TODIM framework, creating the first comprehensive q-rung orthopair fuzzy TODIM method that retains behavioral realism while processing complex fuzzy information. A case study on multi-path transmission scheme selection demonstrates the method's practicality. Comparative experiments and a detailed sensitivity analysis confirm that our framework delivers superior ranking consistency and robustness compared to existing q-rung orthopair fuzzy MCDM methods.
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