• 论文 •    

基于多分类器融合的供应链伙伴动态选择方法

黄梦醒,潘泉,施建宇,张洪才   

  1. 西北工业大学 自动化学院, 陕西西安710072
  • 出版日期:2007-06-15 发布日期:2007-06-25

Dynamic partner selection in supply chain based on multiple classifier fusion

HUANG Mengxing, PAN Quan, SHI Jianyu, ZHANG Hongcai   

  1. School of Automation, Northwestern Polytechnical University, Xi’an710072, China
  • Online:2007-06-15 Published:2007-06-25

摘要: 通过将备选企业的属性看作分类器,将伙伴选择问题转化为不完全、不确定性信息下的分类识别问题。应用多分类器融合规则,建立了供应链伙伴选择的决策模型和方法。该方法不但有效解决了决策信息的不完全性、不确定性和主观性问题,而且有效解决了供应链伙伴的动态选择问题。实例分析结果表明,该方法在供应链伙伴选择和动态选择中具有可行性、有效性和优越性。

关键词: 供应链, 多分类器融合, 伙伴选择, 决策

Abstract: Attributes of each candidate enterprise could be regarded as a classifier, and the partner selection could be transformed into a classification issue with incomplete and uncertain information. A decisionmaking model and a numerical approach of partner selection were proposed based on multiple classifier fusion rules. The new method could not only effectively resolve decisionmaking problem with incomplete, uncertain and subjective information, but also resolve the problem of dynamic partner selection. Case study showed that the new method was feasible, practical and superior.

Key words: supply chain, multiple classifier fusion, partner selection, decisionmaking

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