A DEA-BASED APPROACH TO RANKING MULTI-CRITERIA ALTERNATIVES
We propose a data envelopment analysis (DEA)-based approach to ranking multi-criteria alternatives. We call it "the area of the efficiency score graph" (AES) approach. Unlike the classical DEA score and Dk measure that counts the number of DMUs (alternatives in DEA terminology) that should be removed from the set for each DMU k to become efficient, AES is not fully dependent on relative values of inputs/outputs of the alternatives in the set. It considers the change in efficiency scores of the alternatives while we delete 0,â¦,Dk number of alternatives from the set. The method avoids the negative effect of outliers and crowding in certain areas. It favors DMUs that manage to improve their efficiency scores quickly as we delete units from the set, and also alternatives that maintain high levels of efficiency scores as we delete units. We propose inclusion of weight restrictions into AES to incorporate decision maker preferences into the analysis. We apply our approach to ranking MBA programs. We provide rank lists of MBA programs by both AES and another DEA-based method for comparison. We also use AES scores to place programs in a small number of classes that are preference ordered from the best to the worst.
Data envelopment analysis, multi-objective, integer programming
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