Optimized Captain Selection Using Diffusion-Based Player Behavior Synthesis and Multicriteria Decision Making With Intuitionistic Rough Fuzzy Under Dombi-AHP and PROMETHEE Methods

• Published in: IEEE access Vol. 13; pp. 78471 - 78489
• Main Author: Wang, Ke
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: aggregation operator; Analytic hierarchy process; analytical hierarchy procedure; Analytical models; Caption selection; Decision making; Dombi operations; Estimation; Fuzzy sets; Hierarchies; Leadership; MCDM; multi-criteria decision-making; Multiple criteria decision making; Multiple criterion; Numerical models; Operators; Organizations; Performance measurement; PROMETHEE model; Psychology; Sports; Synthesis
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2025.3564619

The selection of the team captain is an essential decision in team-based sports and professional situations, and it requires an optimized option across multiple criteria. Many existing approaches fail to summarize the difficulties of player behaviors and leadership qualities. In this article, we established a novel model by combining diffusion-based player behavior synthesis with multi-criteria decision-making (MCDM) approach; purposely, we use Dombi aggregation operators (AOs), analytical hierarchy process (AHP), and preference ranking organization method for enrichment evaluation (PROMETHEE) based on an intuitionistic rough fuzzy (IRF) framework. We presented a detailed case study for suitable caption selection based on defined alternatives such as leadership skills, game performance metrics, psychological stability, and tactical awareness. To show the applicability of our methodologies, we discuss numerical examples based on caption selection for football teams. To use the AHP approach, compute the weight vector for criteria. Then, we use our proposed approach, such as intuitionistic rough fuzzy Dombi weighted averaging (IRFDWA) operators and PROMETHEE, to rank candidates. The analysis of Dombi-AHP is an advanced modification of the AHP. It handles the complex MCDM elaborate in captain selection. AHP is selected due to its structured pairwise comparison method, which improves decision accuracy by systematically quantifying subjective decisions. We comprehensively compare our approach with other existing aggregation methods and discuss the sensitive analysis of the proposed theory. Then, provide a solid conclusion.