摘要
研究了基于遗传算法和支持向量机的供应链绩效评价问题。将供应链绩效评价问题用遗传算法进行特征选择并同时对支持向量机参数进行了优化。研究表明该方法能提取出影响供应链绩效的重要属性,减小供应链评价模型的复杂度。应用实例表明基于遗传算法和支持向量机的评价结果从整体上要优于标准支持向量机的评价结果。
This paper studies performance evaluation of supply chain based on Genetic Algorithm（GA） and Support Vector Machine（SVM）.A simultaneous feature selection and SVM parameter optimization algorithm based on GA is used to solve the performance evaluation problem of supply chain.The study shows that important attributes that influence the performance of supply chain are extracted and the complexity of the performance evaluation model of the supply chain is reduced.The numerical example demonstrates that the result of the performance evaluation of supply chain based on GA and SVM is superior to standard SVM.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第1期246-248,共3页
Computer Engineering and Applications
基金
河北省教育厅人文科学研究指导计划项目No.SZ090213~~
