Underground coal mine operations face significant challenges due to the complex and uncertain environments in which they operate. Efficient decision-making in this context is critical for ensuring both safety and productivity. This study addresses the problem of selecting the most suitable operational strategy under uncertainty by applying a multi-criteria group decision-making (MCGDM) framework. We utilize circular Pythagorean fuzzy sets (CPyFS) to better model the vagueness inherent in decision-makers’ (\(\mathcal{D}\)) judgments, offering enhanced flexibility over traditional fuzzy sets (FS) through their circular membership structure. To determine the weights of criteria objectively, we employ the criteria importance through intercriteria correlation (CRITIC) method, and we integrate these weights within the weighted aggregated sum product assessment (WASPA) method for final ranking. Five alternative strategies are evaluated against five operational criteria. The proposed CRITIC–WASPAS method under the CPyFS approach identifies the second alternative as the most effective, with the highest performance score value among all options, and demonstrates competitive performance in terms of accuracy and consistency within the considered case study. A hypothetical case study demonstrates the applicability of the hybrid model in underground coal mining. Sensitivity analysis confirms the robustness of the rankings against changes in criteria weights and various parametric values. Comparative analysis shows that the proposed hybrid model yields identical rankings to other ranking methods. The study offers a methodological decision-support framework for mine managers, enhancing risk assessment and operational planning in uncertain and complex mining environments.
