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Satisficing DEA models under chance constraints. (English) Zbl 0864.90003
Summary: DEA (data envelopment analysis) models and concepts are formulated here in terms of the “P-Models” of chance constrained programming, which are then modified to contact the “satisficing concepts” of H. A. Simon. Satisficing is thereby added as a third category to the efficiency/inefficiency dichotomies that have heretofore prevailed in DEA. Formulations include cases in which inputs and outputs are stochastic, as well as cases in which only the outputs are stochastic. Attention is also devoted to situations in which variations in inputs and outputs are related through a common random variable. Extensions include new developments in goal programming with deterministic equivalents for the corresponding satisficing models under chance constraints.

MSC:
91B06Decision theory
90C15Stochastic programming
90C32Fractional programming
91B38Production theory, theory of the firm (economics)
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