Satisficing data envelopment analysis model with credibility constraints

Based on credibility theory, this paper presents a new class of satisficing data envelopment analysis (DEA) model, in which the inputs and outputs are fuzzy variables and we adopt the concept of fuzzy chance-constrained programming and “satisficing concepts” of H. A. Simon. When the fuzzy inputs and fuzzy outputs are independent trapezoidal fuzzy variables, we transform the satisficing DEA model to its crisp equivalent class and then discuss two basic properties of the proposed satisficing DEA model. At last, a numerical example is given to illustrate the effectiveness of the proposed satisficing DEA model and the relative efficiency is analyzed.