An Interactive Approach for Intuitionistic Fuzzy Data Envelopment Analysis

For accomplishing efficiency analysis and resource planning of organizations in various sectors, data envelopment analysis (DEA) has attracted many researchers' interest. Rather than requiring accurate measurement of input and output data, traditional fuzzy DEA models have been constructed to cope with scenarios when the corresponding data can be represented using conventional fuzzy numbers. Unfortunately, the traditional models are still limited to cases where inputs and outputs take the form of fuzzy numbers, which limits their applicability in real-world scenarios where some inputs and outputs may possess the essence of intuitionistic fuzziness. This paper aims to break the limitation and constructs an interactive approach for intuitionistic fuzzy DEA models, which enables decision makers to present their preferences in the decision-making process. Firstly, this study introduces the comparison rules of intuitionistic fuzzy numbers, thereby incorporates feasibility degrees into the proposed intuitionistic fuzzy DEA model, which enables decision makers to present their preferences for the trade-off between the satisfaction degree of constraints and that of the objective functions. Subsequently, this paper defines the algebraic operation rules for intuitionistic fuzzy numbers, hence constructs operation rules for expected intervals and expected values. Further, by employing comparison rules and operation rules this research transforms the intuitionistic fuzzy DEA model into a linear programming, which facilitates problem-solving. Finally, one illustrative example is employed and compared with an existing one, which shows that our approach has significant advantages over previous approaches.