Three-Way Conflict Analysis and Resolution for Intuitionistic Fuzzy Information Systems via Three-Way Concept Analysis
Han Wang, Yanbing Ju, Enrique Herrera‐Viedma · IEEE Transactions on Cybernetics · 2025
Analyzing conflicts between multiple objects within fuzzy information systems (ISs) and providing effective conflict resolution are challenging tasks due to the complexity and uncertainty of the real world. This article proposes a three-way conflict analysis and resolution model for intuitionistic fuzzy ISs (IFISs) based on three-way concept analysis (3WCA). First, the straight and vertical distances between intuitionistic fuzzy values (IFVs) are defined to obtain an intuitionistic fuzzy probability-credibility distribution. Second, intuitionistic fuzzy optimistic and pessimistic formal contexts are proposed based on two novel binary relations of intuitionistic fuzzy information. Afterward, two intuitionistic fuzzy concept lattices are obtained to analyze the marginal conflict degrees among multiple objects via consistency, inconsistency, and uncertainty attribute sets. By introducing three pairs of thresholds, the trisections of object pairs, objects, and attributes are derived through the three-way decision (3WD) process. Specifically, the maximal alliance unit, minimal conflict unit, and feasible strategy set are identified according to the three-way conflict analysis results. Subsequently, the consistency measure extracted from the intuitionistic fuzzy distance matrix is utilized to rank all feasible strategies. Finally, the experimental results are conducted to verify the effectiveness, superiority, and feasibility of the proposed model.