استفاده از تحلیل پوششی داده‌های ناهموار برای ارزیابی تأمین‌کنندگان، مطالعه موردی: گروه صنعتی ایران ترانسفو

Im this paper, the performance of suppliers is evaluated based on their efficiencies. Evaluation environment is not always precise and we may face imprecise for evaluation indexes values. In this situation, traditional and certain models cannot be employed. For overcoming uncertainty problem, there are different models such as stochastic, statistical, Rough, Fuzzy, etc for solving uncertainty evaluation problems. In this research, DEA and Rough Set Theory (RST) have been integrated and a new hybrid model has been created to evaluate the suppliers under uncertainty situations. Rough Sets Theory is a new approach which uses the concept of approximation. At first, evaluation indexes have been modeled as Rough variables, and then Rough Data Envelopment Analysis model has been created. Then by using the Rough Expected Value, the Rough variables have been converted into a interval under a trust level and Rough Data Envelopment Analysis (RDEA) has been transformed into Interval Data Envelopment Analysis (IDEA). After solving the interval model, every supplier’s efficiency has been demonstrated as an interval and finally by using Herwich approach and under a trust level, Interval Efficiency has been ranked. Proposed technique has been implemented in a Transformator production named Iran Transfo Company