Yager-based operator interval-valued q-rung orthopair fuzzy CRITIC-WASPAS multi-attribute group decision-making method

Abstract Effective multi-attribute group decision-making (MAGDM) in complex scenarios often suffers from inherent challenges, which are unknown expert and attribute weights, and inherent information uncertainty. To overcome these limitations, this paper proposes a CRITIC-WASPAS method for solving MAGDM problems with unknown experts and attribute weights. The method integrates the Yager operator, expert weights, criteria importance through criteria correlation (CRITIC), and the weighted aggregate sum product assessment (WASPAS) decision-making method under interval-valued q-rung orthopair fuzzy sets (IVq-ROFS). Firstly, we extend the Yager weighted average operator (IVq-ROFYWA) and the Yager weighted geometric average operator (IVq-ROFYWG) under the IVq-ROFS framework. Secondly, we derive expert weights for different alternatives to avoid the deficiency of an overall decision-making perspective and attribute weights based on CRITIC under IVq-ROFS. Thirdly, the integrated CRITIC-WASPAS method based on the WASPAS method is introduced. Finally, two distinct domain cases are implemented to illustrate the effectiveness and broad applicability of the proposed CRITIC-WASPAS method. The implementation results across both domains are consistent with experts’ opinions, and the comparison and analysis results show that the CRITIC-WASPAS method is more effective and feasible.