Multi-attribute decision-making based on probabilistic interval-valued dual hesitant fuzzy sets and extended TOPSIS

Multi-Attribute Decision-Making Approach with Interval-Valued T-Spherical Hesitant Fuzzy Sets

Two fundamental aggregation operators, namely the interval-valued T-spherical hesitant fuzzy weighted averaging (IVTSHF-WA) and weighted geometric (IVTSHF-WG) operators, are proposed, and the power Heronian mean is extended to the IVTSHF environment, yielding the IVTSHF-WPHM and IVTSHF-WGPHM operators.

A Hesitant Fuzzy Rough Set-Based Three-Way Decision Model and Its Application in Infectious Disease Diagnosis

Hesitant fuzzy information systems are effective tools for expressing uncertain information. How to solve decision-making problems in hesitant fuzzy information systems is the focus of this paper. Three-way decision and hesitant fuzzy rough sets are effective tools for solving uncertainty problems. Therefore, an improv...

Approach for Dual Probabilistic Linguistic Decision-Making Under Unknown Attribute Weights Based on Archimedean Power Muirhead Mean Operators

Dual probabilistic linguistic term sets (DPLTSs) provide a powerful tool for describing uncertain, hesitant, and bipolar linguistic assessments in complex decision-making settings. Current aggregation methods for dual probabilistic linguistic information still have drawbacks. They can hardly mitigate the interference b...

Multi-attribute decision making based on neighborhood dominance relation of intuitionistic fuzzy ordered information system

Picture Fuzzy Multi-Attribute Decision-Making Approach with Dubois–Prade Aggregation in Industry 6.0

The proposed PFIDPA and PFIDPOWAA operators provide an effective framework for MADM problems involving uncertain, incomplete, and interrelated information and can serve as an efficient decision-support tool for Industry 6.0 adoption and other complex decision-making problems involving uncertain information.

An integrated decision-making framework for prioritizing the barriers and applications in medical digital twins under hesitant fuzzy linguistic environment with stochastic probabilistic distribution

The rapid evolution of digital twins (DTs) technology is reshaping the medical service system. As medical DTs (MDTs) are themselves complex, existing decisionmaking framework often ignored decision-makers’ (DMs’) hesitant fuzzy preference information and subjective cognitive biases. This research develops an integrated...