Fuzzy stochastic data envelopment analysis with application to Base Realignment and Closure (BRAC)

Date

2012-04-26

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Elsevier

Type

Article

Peer reviewed

Yes

Abstract

Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative efficiency of decision-making units (DMUs) on the basis of multiple inputs and outputs. Conventional DEA models assume that inputs and outputs are measured by exact values on a ratio scale. However, the observed values of the input and output data in real-world problems are often vague or random. Indeed, decision makers (DMs) may encounter a hybrid uncertain environment where fuzziness and randomness coexist in a problem. Several researchers have proposed various fuzzy methods for dealing with the ambiguous and random data in DEA. In this paper, we propose three fuzzy DEA models with respect to probability-possibility, probability-necessity and probability-credibility constraints. In addition to addressing the possibility, necessity and credibility constraints in the DEA model we also consider the probability constraints. A case study for the base realignment and closure (BRAC) decision process at the U.S. Department of Defense (DoD) is presented to illustrate the features and the applicability of the proposed models.

Description

Keywords

Data envelopment analysis, Fuzzy random variable, Base realignment and closure, Probability-possibility, Probability-necessity, Probability-credibility

Citation

Tavana, M., Shiraz, R. K., Hatami-Marbini, A., Agrell, P. J. and Paryab, K. (2012) Fuzzy stochastic data envelopment analysis with application to Base Realignment and Closure (BRAC). Expert Systems with Applications, 39 (15), pp. 12247-12259

Rights

Research Institute

Centre for Enterprise and Innovation (CEI)