An improved consistency-driven consensus model under interval-valued neutrosophic preference relations for drone transit station selection in group decision-making

Interval-valued neutrosophic preference relations (IVNPRs), as an extension of interval-valued neutrosophic sets in preference modeling, can represent DMs’ hesitation and uncertainty through interval-form truth, indeterminacy, and falsity membership degrees. However, existing IVNPR-based group decision-making (GDM) models often separate consistency rectification from consensus reaching or cause information loss during ranking. This paper proposes an integrated GDM framework for consistency, consensus, and ranking based on IVNPRs. First, an additive consistency index (ACI) is defined, and a parametric linear programming model is developed to minimize modifications to original preferences. Second, a consensus optimization model is constructed to jointly adjust preferences and determine DM weights while reflecting expert reliability. Third, a likelihood comparison-based ranking method is designed by integrating exponential distance, TOPSIS, and interval inclusion information to reduce information loss. Finally, sensitivity analysis, comparative analysis, ablation analysis, and computational efficiency analysis are conducted to verify the model’s stability, applicability, and scalability. The proposed framework provides a robust tool for intelligent decision-making by preserving original expertise while resolving logical inconsistencies.