A ‎n‎onlinear model for common weights set identification in‎ ‎network Data Envelopment ‎Analysis

‎‎In the Data Envelopment Analysis (DEA) the efficiency of the units‎ ‎can be obtained by identifying the degree of the importance of the‎ ‎criteria (inputs-outputs).In DEA basic models‎, ‎challenges are zero‎ ‎and unequal weights of the criteria when decision‎- ‎making units are‎ ‎evaluated‎. ‎One of the strategies applied to deal with these problems‎ ‎is using common weights of the each input/output in all decision‎ ‎making units (DMUs)‎. ‎In practice the DMUs are containing‎ ‎intermediate process‎. ‎However‎, ‎these units are considered as a black‎ ‎box in DEA basic models‎, ‎disregarding internal process‎. ‎This was‎ ‎the main reason network data envelopment analysis was introduced‎. ‎On‎ ‎the other hand‎, ‎similar challenges mentioned for DEA‎, ‎zero and‎ ‎unequal weights of the criteria‎, ‎exist for network structures as‎ ‎well‎. ‎This paper suggests a common set of the weights for network‎ ‎structures to deal with the above problems using nonlinear models,‎ ‎for general case‎. ‎Also some numerical examples using proposed models‎ ‎are presented.‎‎‎