Favored Target Setting using a Hybrid Fuzzy Goal Programming and Data Envelopment Analysis

Abstract

Data envelopment analysis (DEA) is a method to estimate a relative efficiency of decision making units (DMUs) performing similar tasks in a production system that consumes multiple inputs to produce multiple outputs. The original DEA model does not include a decision maker’s (DM’s) preference structure while measuring relative efficiency. Regarding to relationship between DEA and multiple objective linear programming (MOLP) this paper propose a method based on fuzzy goal programming to incorporate DM’s wishes in evaluation of DMUs then it analyzes the situations that the input-output levels of the estimated benchmark will not or may worsen. A compromised method is suggested that not only considers DM’s wishes in target setting but also improve the efficiency of DMUs while none of input-output levels deteriorate.