A Fuzzy-PROMETHEE Framework for the Multi-Criteria Selection of Dental Implant Biomaterials: A Comparative Analysis of 22 Candidates

The selection of an optimal biomaterial is a critical determinant of the long-term clinical success of dental implants, requiring a careful balance among competing mechanical, biological, and clinical performance criteria. This study develops a comprehensive evaluation framework employing the Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-PROMETHEE II) to conduct a systematic comparative analysis of 22 contemporary biomaterials across eight key criteria: elastic modulus, yield strength, ultimate tensile strength, density, osseointegration potential, corrosion resistance, biostability, and potential side effects. To address the inherent uncertainty in material property data, triangular fuzzy numbers (TFNs) were utilized to model both quantitative property intervals and qualitative linguistic variables—an approach justified by the fact that biomaterial properties are routinely reported as ranges rather than crisp scalar values. The Fuzzy-PROMETHEE method was selected over alternative MCDM approaches because of its capacity for pairwise outranking without the rank-reversal instability characteristic of TOPSIS, and its lower parametric burden compared to AHP when evaluating large alternative sets. The analysis identified the titanium alloy Ti-6Al-4V as the top-performing material, achieving the highest net outranking flow (Φnet = 0.3152), attributable to its uniquely balanced profile of fracture toughness, yield strength, and osseointegration potential. Zirconia ranked sixth (Φnet = 0.1659), reflecting a quantifiable mechanical trade-off relative to metallic alternatives despite its superior aesthetic properties. The robustness of the framework was corroborated by comparative analysis using TOPSIS (relative closeness = 0.839, identical top ranking) and confirmed stable by sensitivity analysis across Osseointegration criterion weight variations from 0% to 50%. This study presents a transparent, evidence-based decision-support tool to assist clinicians in navigating the complex trade-offs inherent in modern implantology.