Enhancing Decision-Making in Ranking Multiple Energy Sources: A Linguistic-Based Multi-Criteria Approach

Energy plays a vital role in sustaining human life and exerting a substantial influence on a nation's economic growth. Assessing diverse energy sources is critical for fostering socio-environmental development and facilitating techno-economic progress. These sources can be classified as renewable (biomass, hydroelectric, solar, wind, and geothermal) or nonrenewable (coal, natural gas, and oil). However, the challenge lies in effectively evaluating and selecting the most suitable energy sources, considering complex linguistic information and multiple criteria. In this study, we propose a linguistic MCGDM approach to assess and rank energy sources in Tunisia. This method effectively handles decision makers' diverse linguistic information. The first phase involves determining criteria weights using the AHP method based on expert opinions in the energy field. Then, the 2-Tuple WASPAS method is applied to evaluate various energy sources. The results provide a ranking of energy policies in Tunisia, from the best to the worst.