基于RS和SVM的动态供应链成员选择算法  

Dynamic Supply Chain Partner Selection Research Based on RS and SVM

作　　者：张学龙[1] 王道平[2] 赵相忠[1] 

机构地区：[1]桂林电子科技大学商学院,广西桂林541004 [2]北京科技大学东凌经济管理学院,北京100083

出　　处：《数学的实践与认识》2014年第6期1-6,共6页Mathematics in Practice and Theory

基　　金：教育部人文社会科学研究青年基金(11YJC630290);广西高等学校科研资助(200103YB050)

摘　　要：良好的成员选择方法是动态供应链平稳运行的重要基础,针对动态供应链成员选择时面临决策属性多且可供决策分析数据样本少的难题,提出了基于粗糙集和支持向量机的动态供应链成员选择算法,核心是应用粗糙集进行属性约简,然后结合支持向量机进行链上成员分类.方法在保证不会降低分类性能的前提下,达到降低数据维数和分类过程中复杂度的目的.Running member operating method is the basement of dynamic supply chain that is smooth running. Aiming at difficulties in selecting dynamic supply chain partner, a partner selection model based on Rough Sets and Support Vector Machine has been proposed in this paper in order to solve the problem that decision-making attributes are varies and the sample data used for decision-making and analysis are insufficient. The core point of this model is the use of rough sets theory to pick out the important attributes, and then support vector machine is used for customer classification. This method that does not affect classification performance can reduce the data dimensions and the complexity in classification process.

关 键 词：动态供应链 成员选择 粗糙集 支持向量机 

分 类 号：F274[经济管理—企业管理] TP18[经济管理—国民经济]