A new last aggregation compromise solution approach based on TOPSIS method with hesitant fuzzy setting to energy policy evaluation

Utilizing renewable energies is one of the most important issues for economical and social significance in future human life. Choosing the best renewable energy among all other candidates is very important in this area. To address the issue, multi-criteria group decision making (MCGDM) methods with imprecise information could be employed to solve these problems. The aim of this paper is to propose a new compromise solution approach based on technique for order preference by similarity to ideal solution (TOPSIS) method under evaluations of a group of experts with hesitant fuzzy information. The hesitant fuzzy set (HFS) is a new fuzzy set which could help the experts by providing some membership degrees for renewable energy candidates under the evaluation criteria to margin of errors. Also, weights of each expert and criterion are determined by proposing extended hesitant fuzzy entropy and maximizing deviation methods based on hesitant fuzzy Euclidean-Hausdorff distance measure. In addition, the judgments (preferences) of experts are aggregated in the final step to prevent the loss of data. Finally, an illustrative example about the energy policy selection is presented to demonstrate the performance of the proposed decision approach. Also, a comparative analysis is provided with the recent decision methods of the literature to show the capability of the proposed approach.