Abstract
Data Envelopment Analysis (DEA) is a linear programming based model which evaluates the relative efficiency of Decision Making Units (DMUs), with multiple inputs and outputs. Conventional DEA evaluates DMUs with their own weights and separates them into efficient and inefficient. To provide a full ranking of DMUs or select one of them (as the most preferred one), more discrimination is necessary. This paper presents a method that ranks extreme efficient units by comparing the volumes of their optimal weight sets, approximately, through generating some random weight vectors. To illustrate the proposed method, some numerical examples are provided.
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