Data Envelopment Analysis (DEA) is a non-parametric technique for evaluating the efficiency of\nDecision Making Units (DMUs) with multiple inputs and outputs. Evaluating performance supply\nchain is one of the uses of DEA. But hence, the traditional DEA models treat with each DMU as a\nââ?¬Å?black boxââ?¬Â, thus, the performance measurement may be not effective. So, there are necessities for\nnetwork DEA models. The primary condition for the use of DEA models is that the data are exact.\nBut in the real word, we are often conformed to vague and uncertain data and performance evaluation\nby usual methods in the presence such data may lead errors in decision-making process, so for\nmaking applied decision and more adaptive to real word, it is undeniable need for fuzzy logic to\nevaluate the efficiency of unit. In this paper, at first, a new non-radial network DEA model for\nevaluating performance supply chain is introduced, by considering intermediate production. Its\noptimal solution can separate inefficient and strong efficient DMUs, and finally we solve this model\nwhen the all data are fuzzy numbers.
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