A new three-way multi-attribute decision-making with objective risk avoidance coefficients based on q-rung orthopair fuzzy pre-order relations

Three-way multi-attribute decision-making (3W-MADM) in fuzzy environments offers a more cognitively valid and risk-averse alternative to traditional decision-making frameworks. However, current studies reveal several challenges, including the influence of subjective factors, low discrimination rates in distance measures, and high redundancy levels in 3W-MADM. To address these issues, we establish a new 3W-MADM model with objective risk avoidance coefficients based on q-rung orthopair fuzzy pre-order relations. The research goals involve reducing subjective biases, enhancing distance measure discrimination, and improving 3W-MADM utility. First, to reduce the influence of subjective factors on decision-making, we propose an innovative method for calculating risk avoidance coefficients. Second, this paper suggests a new q-rung othorpair fuzzy distance measure with high discrimination rate and introduces the distance measure into the pre-order relations as a way to objectively compute the 3W-MADM conditional probabilities. Third, q-rung othorpair fuzzy sets (q-ROFSs) is extended to 3W-MADM. To further demonstrate its practical applicability, a novel approach for converting large-scale real datasets into q-ROFSs is introduced, and numerous experiments have been conducted in psychological health assessment to validate the proposed method’s rationality and superiority. Finally, the analysis of various experimental results indicates that our method reduces subjective influence and redundancy level and improves discrimination rate of distance measure.