| 基于SPSS的自适应供应链节点配置 |
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| 引用本文： | 黄辉,梁工谦.基于SPSS的自适应供应链节点配置[J].工业工程,2012(1):39-43. |
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| 作者姓名： | 黄辉 梁工谦 |
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| 作者单位： | 西北工业大学管理学院 |
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| 基金项目： | 陕西省社会科学基金资助项目(10Q056);西北工业大学人文社科与管理振兴基金项目(RW201109) |
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| 摘 要： | 在简化的二阶供应链基础上,使用SPSS Clementine构建了自适应供应链节点配置的数据流模型,把历史订单数据的有效信息(采购量、提前期、价格等)作为训练数据,使用C5.0算法模型进行学习与训练,得到最佳供应商选择的规则集。并使用收益图和提升图对C5.0决策模型进行评价,结果表明该模型质量较好。然后使用模拟订单数据进行验证,并得到了最优的供应商选择结果,且置信度达到了满意水平。
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| 关 键 词： | 自适应供应链 机器学习 供应链管理 |
SPSS-based Research on Adaptive Supply Chain Configuration |
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| Huang Hui,Liang Gong-qian.SPSS-based Research on Adaptive Supply Chain Configuration[J].Industrial Engineering Journal,2012(1):39-43. |
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| Authors: | Huang Hui Liang Gong-qian |
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| Affiliation: | (School of Management,Northwestern Polytechnic University,Xi′an 710072,China) |
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| Abstract: | To adapt to the market changes,a supply chain should be reconfigured from time to time.The supply chain configuration is discussed in this paper and the study is conducted based on the simplified two-tier supply chain.By using SPSS Clementine software,a data flow model is built for the adaptive supply chain configuration(ASCC).By using data that include information of purchase quantity,lead time,and price of order as input of the model for training,a rule set for best supplier selection can be obtained.The ASCC model is evaluated by using gains chart and lift chart,result shows that the model is effective.A set of virtual order data is used to test the ASCC model.After training,a supplier is selected with a satisfactory confidence level. |
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| Keywords: | adaptive supply chain machine learning supply chain management |
| 本文献已被 CNKI 等数据库收录！ |
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