Weighted Group Role Assignment Based on Three-Way Conflict Analysis With Interval-Valued Intuitionistic Fuzzy Numbers

Abstract

Role-based collaboration (RBC) has become a crucial computational approach for task allocation and team coordination, yet three critical research gaps remain unresolved. First, while existing methods treat role importance uniformly, real-world scenarios require differentiated prioritization of roles, which is a gap addressed through role weight vectors that dynamically adjust task significance. Second, current qualification matrices that directly specify agent capabilities lack mechanisms to handle assessment uncertainties, leading this article to propose a novel determination method using intuitionistic fuzzy numbers for robust capability modeling. Third, the absence of systematic conflict categorization frameworks motivates our three-way conflict analysis (TWCA) method that classifies conflicts through hierarchical comparisons of agent competency. Drawing from these considerations, the article presents the weighted group role assignment (GRA) with conflicting constraints problem, aiming to overcome the identified challenges through environments-classes, agents, roles, groups, and objects (E-CARGO) framework. The proposed approach is tested and validated through a series of experiments and comparative analyses to demonstrate its efficacy.