Positive and normative use of Fuzzy DEA-BCC models: A critical view on NATO enlargement

摘要: Data envelopment analysis (DEA) is a widely used mathematical programming approach for comparing the input and output of set comparable decision-making units (DMUs) by evaluating their relative efficiency. The traditional DEA methods require accurate measurement both inputs outputs. However, real evaluation DMUs often characterized imprecision uncertainty in data definitions measurements. development fuzzy (FDEA) with imprecise ambiguous has extended scope application efficiency measurement. purpose this paper to develop framework BCC model measuring crisp interval efficiencies environments. We use an α-level convert Banker, Charnes, Cooper (BCC) (variable returns scale) into model. Instead equality (or inequality) two intervals, we define variable satisfy our constraints maximize value. present numerical example show similarities differences between solution solutions obtained from four literature. In addition, case study NATO enlargement presented illustrate applicability proposed method.