The evidential reasoning approach for renewable energy resources evaluation under interval type-2 fuzzy uncertainty

Selecting the right renewable energy resources (RESs) is emerging as a solution to alleviate energy crisis and environmental pollution. Due to the limitation of human knowledge and the complexity of reality, the selection process usually involves multiple uncertainties. In this paper, an interval type-2 fuzzy evidential reasoning approach is proposed to solve the RESs evaluation problem with uncertain information. First, the linguistic terms involved in the RESs evaluation process are encoded into the interval type-2 fuzzy sets (IT2FSs). Second, a new interval type-2 fuzzy distance model is developed to measure the distance between the IT2FSs. After obtaining the distance, two new information transformation techniques are respectively defined to transform the IT2FSs and the crisp numbers into the interval belief structures. Then, an interval type-2 fuzzy entropy measure is proposed to determine the weights of attributes and the corresponding axioms are proved mathe-matically. Finally, the interval expected utility of each alternative is generated by a pair of nonlinear optimization models and then ranked by an enhanced minimax regret approach. A case study about the RESs evaluation is provided to illustrate the effectiveness of the proposed approach, comparisons and discussions are also conducted to show the superiority. (c) 2021 Elsevier Inc. All rights reserved.