Evaluating the performance and ranking of DMUs: A fuzzy bounded DEA approach
Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. Unfortunately, the existing DEA models are limited to crisp parameters. To deal with data uncertainty in real-life problems, the notion of fuzziness has been often utilizing in the context of decision sciences such as DEA. In this study, we put forward a fuzzy DEA model with the fuzzy inputs and fuzzy outputs to obtain the interval efficiency using a common set of weights approach. First, we construct a fuzzy anti-ideal DMU and its best relative efficiency is measured. Second, we propose a pair of the models to acquire the upper and lower bounds of the efficiency. Third, we use a method to rank the interval efficiency of the DMUs. Finally, we present a numerical example to demonstrate the applicability of the proposed model.
Citation : Hatami-Marbini, A., Gholami, K. and Ghelej Beigi, Z. (2014) Evaluating the performance and ranking of DMUs: A fuzzy bounded DEA approach. 44th International Conference on Com puters and Industrial Engineering 2014 (CIE’44) and 9th International Symposium on Intelligent Manufacturing and Se rvice Systems 2014 (IMSS’14) Istanbul, Turkey 14-16 October 2014
Research Institute : Centre for Enterprise and Innovation (CEI)