Supplier Selection Based on a Neural Network Model Using Genetic Algorithm

In this paper, a decision-making model was developed to select suppliers using neural networks (NNs). This model used historical supplier performance data for selection of vendor suppliers. Input and output were designed in a unique manner for training purposes. The managers´ judgments about suppliers were simulated by using a pairwise comparisons matrix for output estimation in the NN. To obtain the benefit of a search technique for model structure and training, genetic algorithm (GA) was applied for the initial weights and architecture of the network. The suppliers´ database information (input) can be updated over time to change the suppliers´ score estimation based on their performance. The case study illustrated shows how the model can be applied for suppliers´ selection.