Data envelopment analysis (DEA) is a non-parametric approach for measuring the efficiency of decision\nmaking units (DMUs) that use multiple inputs in order to produce multiple outputs. In most real\napplications, DMUs have a two-stage network process which can be used for management of organizations\nsuch as hospitals, insurance companies, banks, and etc. The data are crisp in the standard DEA model\nwhereas there are many problems in the real life that data may be uncertain. Thus, in this paper, we\npropose a model to estimate the efficiency of DMUs with a two-stage structure and the inputs and outputs\nof DMUs are fuzzy data. Also, DEA can be used to allocate resources; therefore, we propose a new\nmethod to allocate resources for DMUs with a two-stage structure and fuzzy data. The main aim of this\nallocation is preserving the efficiency score of DMUs. We illustrate the applicability of models by using a\nnumerical example.
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