Abstrakt

Evaluation of Efficiency in DEA Models Using a Common Set of Weights

Shinoy George, Sushama C M

Data Envelopment Analysis is a well-known OR technique for evaluating the relative efficiency of a set of similar decision making units (DMUs).In the classical DEA models, each DMU assigns weights to the factors so as to maximize efficiency. This is unacceptable, since the same factors have widely different weights for each DMU. So, in order to discriminate efficient and non-efficient DMUs properly, a common set of weights need to be used. In this paper, a multiobjective programming model is developed to derive a common set of weights. Solution methodology uses fuzzy programming. The method is illustrated through an example in which data sets are taken from the previous research on DEA’s discriminating power and weight restriction.