An ERP software selection process with using artificial neural network based on analytic network process approach

An enterprise resource planning (ERP) software selection is known to be multi attribute decision making (MADM) problem. This problem has been modeled according with analytic network process (ANP) method due to Tact that it considers criteria and sub criteria relations and interrelations in selecting the software. Opinions of many experts are obtained while building ANP model for the selection ERP then opinions arc reduced to one single value by methods like geometric means so as to get desired results. To use ANP model for the selection of ERP for a new organization, a new group of expert's opinions are needed. In this case the same problem will be in counter. In the proposed model, when ANP and ANN models are setup, an ERP software selection can be made easily by the opinions of one single expert. In that case calculation of geometric mean of answers that obtained from many experts will be unnecessary. Additionally the effect of subjective opinion of one single decision maker will be avoided. In terms of difficulty, ANP has some difficulties due to eigenvalue and their limit value calculation. An ANN model has been designed and trained with using ANP results in order to calculate ERP software priority. The artificial neural network (ANN) model is trained by results obtained from ANP. It seems that there is no any major difficulty in order to predict software priorities with trained ANN model. By this results ANN model has been come suitable for using in the selection of ERP for another new decision. (C) 2008 Elsevier Ltd. All rights reserved.