Title
Fuzzy stochastic data envelopment analysis with application to base realignment and closure (BRAC)
Document Type
Article
Publication Date
11-1-2012
DOI
https://doi.org/10.1016/j.eswa.2012.04.049
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.
Language
English
Recommended Citation
Tavana, Madjid; Shiraz, Rashed Khanjani; Hatami-Marbini, Adel; Agrell, Per J.; and Paryab, Khalil, "Fuzzy stochastic data envelopment analysis with application to base realignment and closure (BRAC)" (2012). Business Systems and Analytics Faculty Work. 242.
https://digitalcommons.lasalle.edu/bsa_faculty/242
Comments
Tavana, M., Khanjani Shiraz, R., 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, Vol. 39, No. 15, pp. 12247–12259.