Performance assessment of decision-making units using an adaptive neural network algorithm: one period case

This study proposes a nonparametric method based on adaptive neural network (ANN) technique for measuring efficiency of decision making units (DMUs) in one period case as a complementary tool for the ANN-based efficiency methods in the previous studies. In previous studies, there are needed to have large volume of data, and so the proposed method in this study is more applicable because it can be used for the cases which have no historical data. In fact, a limitative weakness of the ANN-based efficiency methods about applying them for these cases is removed. So, it can be a competitive method to the other common tools for measuring efficiency. By noting the importance of flexible manufacturing system, this study presents a decision-making model for optimization of operators’ allocation in cellular manufacturing system by computer simulation. The methodology is illustrated through its application on a previously reported dataset. It was found out that ANN provides more robust results and identifies more efficient units than the conventional methods since better performance patterns are explored.

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