مشخصات پژوهش

Congestion is an important issue in every field of sciences and occurs when one or more outputs can be increased by reducing one or more inputs, without worsening any other input or output. So far all of the presented models to solve the congestion problem are based on the traditional DEA models which treat any DMU as a black-box and ignore intermediate products. Therefore, to overcome the above challenge, the NDEA models were introduced that consider all of the intermediate flows. Among the different models with a variety of applications, there was not much attention to the congestion issue in the NDEA models. In this study, we have focused on identifying the evidence of the congestion in the two-stage structures. To achieve this aim, we propose new models for measuring congestion in each division of the network. The proposed models able to detect which inputs cause congestion in each stage. Moreover, the most important advantages of these models are that they can make difference between the inefficient and congestion concepts. To test the reliability of the proposing models, we have applied them in the health network structure.