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Author (up) Çelebi, D.; Bayraktar, D. doi  openurl
  Title An integrated neural network and data envelopment analysis for supplier evaluation under incomplete information Type Journal Article
  Year 2008 Publication Expert Systems with Applications Abbreviated Journal  
  Volume 35 Issue 4 Pages 1698-1710  
  Keywords Supplier evaluation; Neural networks; Data Envelopment Analysis (DEA )  
  Abstract Supplier evaluation and selection are critical decision making processes that require consideration of a variety of attributes. Several studies have been performed for effective evaluation and selection of suppliers by utilizing several techniques such as linear weighting methods, mathematical programming models, statistical methods and AI based techniques. One of the successful evaluation methods proposed for this purpose is data envelopment analysis (DEA), that utilizes techniques of mathematical programming to evaluate the performance of a set of homogeneous decision making units, when multiple inputs and outputs need to be considered. It is often complicated, costly and sometimes impossible to acquire all necessary information from all potential suppliers to attain a reasonable set of similar input and output values which is an essential for DEA. The purpose of this study is to explore a novel integration of neural networks (NN) and data envelopment analysis for evaluation of suppliers under incomplete information of evaluation criteria.  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ admin @ CelebiBayraktar2008 Serial 4046  
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