The Optimistic-Pessimistic Ranking in the Chance Constrained DEA
نویسندگان
چکیده
Recently, Khodabakhshi and Aryavash have introduced a ranking method [Applied Mathematics Letters, 25 (2012) 2066-2070.], which is based on an optimistic-pessimistic approach of data envelopment analysis (DEA). This method ranks all decision making units according to a combination of their minimum and maximum possible efficiency scores which are determined by solving two linear programming models. This method can only rank decision making units (DMUs) with deterministic input and output indexes, whereas in the real application the data are often imprecise. In this paper, the chance constrained version of this ranking method is presented. KeywordsData envelopment analysis, Stochastic ranking model, Chance constrained programming, Optimistic-pessimistic approach
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