TY - JOUR
T1 - Fuzzy stochastic data envelopment analysis with application to base realignment and closure (BRAC)
AU - Tavana, Madjid
AU - Khanjani Shiraz, Rashed
AU - Hatami-Marbini, Adel
AU - Agrell, Per J.
AU - Paryab, Khalil
N1 - Funding Information:
This research was supported in part by the U.S. Naval Research Laboratory Grant No. N00014-08-1-0160 .
PY - 2012/11/1
Y1 - 2012/11/1
N2 - 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.
AB - 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.
KW - Base realignment and closure
KW - Data envelopment analysis
KW - Fuzzy random variable
KW - Probability-credibility
KW - Probability-necessity
KW - Probability-possibility
UR - http://www.scopus.com/inward/record.url?scp=84863087920&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2012.04.049
DO - 10.1016/j.eswa.2012.04.049
M3 - Article
AN - SCOPUS:84863087920
VL - 39
SP - 12247
EP - 12259
JO - Expert Systems with Applications
JF - Expert Systems with Applications
SN - 0957-4174
IS - 15
ER -