Title: A fully fuzzified data envelopment analysis model

Authors: Adel Hatami-Marbini, Madjid Tavana, Alireza Ebrahimi

Addresses: Louvain School of Management, Center of Operations Research and Econometrics (CORE), Universite Catholique de Louvain, 34 Voie du Roman Pays, B-1348 Louvain-le-Neuve, Belgium. ' La Salle University, Philadelphia, PA 19141, USA. ' Faculty of Industrial Engineering, Productivity and System Management, Islamic Azad University of South Tehran Branch, Tehran, Iran

Abstract: In the conventional data envelopment analysis (DEA), all the data assumes the form of crisp numerical values. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Some researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA by constructing linear programming (LP) models with |partial| fuzzy parameters. The main purpose of this study is to evaluate the performance of a set of decision making units (DMUs) in a fully fuzzified environment. We propose a novel fully fuzzified DEA (FFDEA) model by utilising a fully fuzzified LP (FFLP) model, where all decision parameters and variables are fuzzy numbers. The contribution of this paper is threefold: first, we consider ambiguous, uncertain and imprecise input and output data in DEA; second, we address the gap in the fuzzy DEA literature for solutions to fully fuzzified problems; and third, we present a numerical example to demonstrate the applicability and efficacy of the proposed model.

Keywords: data envelopment analysis; DEA; fuzzy decision parameters; fuzzy variables; fuzzy efficiency; fuzzy linear programming; FLP; imprecise data; ambiguous data; decision making units; DMUs; uncertainty; modelling.

DOI: 10.1504/IJIDS.2011.041586

International Journal of Information and Decision Sciences, 2011 Vol.3 No.3, pp.252 - 264

Published online: 30 Oct 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article