Supplier selection based on a neural network model using genetic algorithm

Davood Golmohammadi, Robert C. Creese, Haleh Valian, John Kolassa

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1504-1519
Number of pages16
JournalIEEE Transactions on Neural Networks
Issue number9
StatePublished - 2009

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence


  • Decision making
  • Decision-making models
  • Fuzzy set
  • Genetic algorithms
  • Genetic algorithms (GAs)
  • Neural networks (NNs)
  • Supplier selection


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