Applying the Pythagorean Fuzzy Set-based and the MULTIMOORA Method to Address Renewable Energy Source Selection Issues

Energy policy plays a pivotal role in assessing economic development in nations worldwide. As environmental awareness grows, selecting renewable energy has become more important. Renewable energy sources are significant tools in reducing carbon emissions and environmental pollution. The challenges related to selecting renewable energy sources, which involve multiple experts and multiple evaluation criteria, fall under complex multi-criteria group decision-making (MCGDM) issues. However, the typical MCGDM method often faces limitations in simultaneously processing both quantitative and qualitative data, handling information presented in linguistic terms sets provided by experts at varying levels, and processing cognitive content information effectively, resulting in erroneous evaluation results. To address these limitations, this study integrates the Pythagorean fuzzy set (FS) with the multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) approach to solve renewable energy source selection problems. In practical application, this study applied the desirable energy source selection case to validate the accuracy and rationality of the proposed novel MCGDM approach. The computational experiments were analyzed and compared using the simple additive weighting, intuitionistic FS, and MULTIMOORA approaches. The experimental results reveal that the proposed novel MCGDM method excels in versatility in handling fuzzy information, can simultaneously treat qualitative and quantitative data, and can handle linguistic term sets with varied information levels.