Ambiguous Fuzzy Averaging Operator Based Decision-Making Approach with Application to Classification of Renewable Energy Sources

A renewable-energy-source-selection (RES-selection) is a complex multi-criteria-decision-making (MCDM) challenge to select the optimal RES on the basis of some criteria. The complexity exists due to the relationship of miscellaneous contradictory standards, unknown and vague information. To deal with inherent uncertainties and vague information, the theory of Ambiguous intuitionistic fuzzy set (AIFS) has been introduced recently. This study is an effort to provide a RES-classification method under the AIFS environment. This can be achieved by proposing new aggregation operators, namely the ambiguous-intuitionistic weighted-averaging (AI- W A) and the ambiguous-intuitionistic ordered-weighted-averaging (AI-OW A), to fuse AIFNs input information. Based on the proposed the AI-WA and the AI-OW A operators, we develop an approach for RES- classification problem and applied it to classify four considered RESs.