<p>Group decision-making (GDM) problems often involve various uncertainties, and accurately characterizing the opinion information of decision makers (DMs) significantly impacts the reasonableness of results. Distributed preference relation (DPR) is an effective probabilistic linguistic expression scheme for uncertain pairwise comparisons. However, the consistency analysis of DPR has not yet discussed the cases of fuzzy and interdependent evaluation grades, as well as ordinal inconsistency. Existing studies about ordinal consistency don’t sufficiently conform to DMs’ willingness and rarely manage the consistency of collective opinions. To this end, we first propose novel possibility and distance formulas for fuzzy DPR (FDPR) to measure priorities and differences between assessments, respectively. Thereafter, the consistency of FDPRs is developed from the perspectives of preference order and intensity, where the corresponding ordinal consistency considers the effects of preference strength and inferior preference relations. For different decision-making needs, an interactive satisfactory consistency reaching algorithm is designed to process varying preference modification willingness of DMs, while an optimization method addresses inconsistencies for time-urgent decisions. Then, the weights of DMs are dynamically updated based on the social trust network and DMs’ confidence levels reflected by the proposed entropy measure. A consensus-reaching algorithm with consistency control is presented to preserve the initial opinions as much as possible. Therefore, a comprehensive framework for individual consistency and group consensus reaching in fuzzy GDM is constructed by integrating DMs’ preferences and trust relationships. The applicability and effectiveness of the proposed method are demonstrated through an example of lifecycle quality assessment, sensitivity analyses, and comparative analyses.</p>