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Neural Computing and Applications

, Volume 27, Issue 3, pp 707–725 | Cite as

An integrated model for green supplier selection under fuzzy environment: application of data envelopment analysis and genetic programming approach

  • Alireza Fallahpour
  • Ezutah Udoncy OluguEmail author
  • Siti Nurmaya Musa
  • Dariush Khezrimotlagh
  • Kuan Yew Wong
Original Article

Abstract

Supplier evaluation plays a critical role in a successful supply chain management. Hence, the evaluation and selection of the right suppliers have become a central decision of manufacturing business activities around the world. Consequently, numerous individual and integrated methods have been presented to evaluate and select suppliers. The current literature shows that hybrid artificial intelligence (AI)-based models have received much attention for supplier evaluation. Integrated data envelopment analysis–artificial neural network (DEA–ANN) is one of the combined methods that have recently garnered great attention from academics and practitioners. However, DEA–ANN model has some drawbacks, which make some limitation in the evaluation process. In this study, we aim at improving the previous DEA–AI models by integrating the Kourosh and Arash method as a robust model of DEA with a new AI approach namely genetic programming (GP) to overcome the shortcomings of previous DEA–AI models in supplier selection. Indeed, in this paper, GP provides a robust nonlinear mathematical equation for the suppliers’ efficiency using the determined criteria. To validate the model, adaptive neuro-fuzzy inference system as a powerful tool was used to compare the result with GP-based model. In addition, parametric analysis and unseen data set were used to validate the precision of the model.

Keywords

Green supplier selection Data envelopment analysis (DEA) Artificial intelligence Genetic programming (GP) Parametric analysis 

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Copyright information

© The Natural Computing Applications Forum 2015

Authors and Affiliations

  • Alireza Fallahpour
    • 1
  • Ezutah Udoncy Olugu
    • 1
    Email author
  • Siti Nurmaya Musa
    • 1
  • Dariush Khezrimotlagh
    • 2
  • Kuan Yew Wong
    • 3
  1. 1.Department of Mechanical Engineering, Faculty of EngineeringUniversity of MalayaKuala LumpurMalaysia
  2. 2.Department of Applied Statistics, Faculty of Economics and Administration BuildingUniversity of MalayaKuala LumpurMalaysia
  3. 3.Department of Manufacturing and Industrial Engineering, Faculty of Mechanical EngineeringUniversiti Teknologi Malaysia (UTM)SkudaiMalaysia

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