Fuzzy AHP‐TOPSIS Framework for Rock Mass Classification Based on RMQR Criteria

A fuzzy model was developed by applying a triangular fuzzy number (TFN)-based fuzzy AHP–TOPSIS methodology to the Rock Mass Quality Rating (RMQR) classification system. The six parameters defined in the original RMQR system were adopted as evaluation criteria. Expert-assigned scores were expressed as fuzzy values, and the criterion weights were determined using the fuzzy AHP method. Rock mass quality classes were then identified using the TOPSIS technique based on the calculated closeness coefficients. The proposed model was tested on 11 different rock mass media. The outcomes of the proposed model were found to be consistent with those of the RMQR system in 10 of these cases. The remaining medium was identified as being close to the classification boundary of the system. A comparative evaluation was conducted using the RMR classification system to provide a more precise assessment for this borderline case. As a result of this comparison, it was found that the proposed model facilitates the decision-making process and optimizes support recommendations for cases located at classification boundaries, which typically influence professional judgment. The reliability of the model was further confirmed by a Spearman’s rank correlation coefficient of 0.995, which indicated strong agreement with the RMQR system. Based on these findings, the proposed model is considered to have potential for widespread application in the planning of engineering structures to be constructed in rock environments.