Intuitionistic fuzzy multiple attribute decision making method based on a parametric piecewise score function

Abstract

The score function and aggregation operator provide the theoretical basis for intuitionistic fuzzy multiple attribute decision making (MADM), where the role of the score function is to compare and rank the intuitionistic fuzzy numbers (IFNs), and the role of the aggregation operator is to integrate the evaluation information. In view of that, this paper proposes a new score function and aggregation operator, and a new intuitionistic fuzzy MADM method. It first constructs a parametric piecewise score function and discusses the influence of hesitancy degree and the parameter λ on it. Moreover, some properties of the constructed score function are discussed, including the monotonicity, maximum, minimum, and range. Then, it introduces a intuitionistic fuzzy modified Einstein aggregation (IFMEWA) operator and proves monotonicity, idempotency and boundedness of IFMEWA operator. Finally, combined with the constructed score function and IFMEWA operator, it proposes a new intuitionistic fuzzy MADM method.