1st International ICST Workshop on Knowledge Discovery and Data Mining

Research Article

Study on the Application of SVM in Supplier Primary Election

  • @INPROCEEDINGS{10.4108/wkdd.2008.2636,
        author={Lili Cai and Fugeng Shong and Deling Yuan},
        title={Study on the Application of SVM in Supplier Primary Election},
        proceedings={1st International ICST Workshop on Knowledge Discovery and Data Mining},
        publisher={ACM},
        proceedings_a={WKDD},
        year={2010},
        month={5},
        keywords={},
        doi={10.4108/wkdd.2008.2636}
    }
    
  • Lili Cai
    Fugeng Shong
    Deling Yuan
    Year: 2010
    Study on the Application of SVM in Supplier Primary Election
    WKDD
    ACM
    DOI: 10.4108/wkdd.2008.2636
Lili Cai1,*, Fugeng Shong1, Deling Yuan1
  • 1: Glorious Sun School of Business and Management, Donghua University, Shanghai, P.R China, 200051
*Contact email: clilyai@163.com

Abstract

Supplier selection is one of the most important things in supply chain management, the process of choosing a suitable supplier will effect enterprise’s production and quality directly. This article puts forward a two-stage model of supplier selection based on analysis the problem of supplier management. It plots out the process as primary election stage and well-chosen stage, and builds up seven criteria to evaluate suppliers in primary election phase. Then, this context uses support vector machine to select suppliers and pays attention to two kinds of error — treat candidate supplier as non-candidate supplier and treat non-candidate supplier as candidate supplier. At last, a numerical simulation is used to explain selection of kernel function and sample training; the result reveals that this new method is practical and realistic and could reduce selection time.