Group decision-making method based on Pythagorean fuzzy rough numbers

Occupational noise is one of the most significant disadvantages of industrialization. The impact of noise pollution on workers results in hearing loss and a variety of other problems. Precautions should be taken to protect workers from the harmful effects of occupational noise. In this study, we propose a multi-criteria group decision-making (MCGDM) strategy to select the best method to reduce occupational noise. Correspondingly, its main theoretical goal is the design of a novel MCGDM technique that extends the weighted aggregation and product assessment (WASPAS) method to become operational with Pythagorean fuzzy rough numbers. The WASPAS method is an objective tool that allows for effective implementation in all scenarios involving decision-making. In MCGDM, its integration with the Analytical Hierarchy Process (AHP) leverages the precision of AHP in criterion weighting and the proficiency of WASPAS in ranking of alternatives, yielding more credible results. The step-by-step process of the proposed PFR-AHP-WASPAS model is presented in a simplified form, and also in a visually appealing flowchart. On a more practical level, we apply this model to a numerical exercise that identifies the most effective strategies for mitigating occupational noise in Pakistani workplaces. Afterwards, we conduct a thorough comparison of the new model with existing methods, including the PFRN-based AHP-TOPSIS method and the fuzzy AHP-WASPAS model. This comparative analysis evaluates the suitability of the decisions provided by the new technique. We also conduct sensitivity analysis to check the robustness and stability of its recommendations.