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Keywords:
data envelopment analysis (DEA); interval data; interval DEA model; common weight
data envelopment analysis (DEA); interval data; interval DEA model; common weight
Summary:
The traditional data envelopment analysis (DEA) model can evaluate the relative efficiencies of a set of decision making units (DMUs) with exact values. But it cannot handle imprecise data. Imprecise data, for example, can be expressed in the form of the interval data or mixtures of interval data and exact data. In order to solve this problem, this study proposes three new interval DEA models from different points of view. Two examples are presented to illustrate and validate these models.
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