An M-Polar Fuzzy Five-Way Decision-Making Framework with Modified Hamacher Aggregation for Carbon Emission Reduction Assessment

The paper presents a new Five-Way Decision Model (5WDM) that is founded on M-Polar Fuzzy Numbers (MPFNs) and a revised version of the Hamacher aggregation operator to improve decision-making in case of uncertainty in carbon emission reduction. The suggested framework appraises major mitigation options such as carbon capture, renewable energy, energy efficiency improvement, green transportation, and waste-to-energy conversion systematically through the use of probabilistic criteria to address uncertainty and interdependence between attributes. It generates a reformulated Hamacher operator that enhances the aggregation behavior by having a more adaptable representation of the truth, indeterminacy, and falsity elements in the MPFN setting and leads to a more stable and discriminative ranking result. The model also breaks down alternatives into five regions of decision-making, which are fully accepted, partially accepted, boundary, partially rejected, and fully rejected, offering a more efficient and understandable classification scheme than traditional methods. The superiority of the proposed method compared to the current fuzzy and neutrosophic frameworks is confirmed by the comparative and sensitivity analysis in the three aspects of robustness, consistency, and flexibility. The findings mention renewable energy as the most viable means of mitigating carbon emissions. On the whole, the analysis provides a mathematically sound and versatile decision model that can be generalised to three-way or binary models, to make informed policymaking in complicated environmental systems.