Journal
APPLIED MATHEMATICS AND COMPUTATION
Volume 162, Issue 3, Pages 1265-1277Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2004.03.007
Keywords
data envelopment analysis; optimization; imprecise data
Categories
Ask authors/readers for more resources
Data envelopment analysis (DEA) evaluates the efficiency of decision making units With Multiple inputs and outputs. In most applications of DEA, presented in literature, the models presented are designed to obtain a single measure of efficiency where all inputs and Outputs are known exactly. In many instances, however, the decision making units involved may perform several different functions, or can be separated into different components and some inputs and outputs are unknown decision variables such as bounded data and ordinal data. In such situations, inputs are often shared among those components and all components play all important role in producing some outputs. In this case, the standard DEA model becomes a non-linear program. We develop in this paper, all alternative approach for dealing with imprecise data in multi-component efficiency measurement in DEA that preserves the linearity of DEA model. (C) 2004 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available