基于优化支持向量机的供应链竞争力评价方法  

Supply Chain Competitiveness Evaluation Method Based on Optimized Support Vector Machine

作　　者：钟夫 郭建胜[1] 张斯嘉[1] 王族统[1] 

机构地区：[1]空军工程大学装备管理与安全工程学院,西安710051

出　　处：《计算机科学》2015年第B11期27-31,共5页Computer Science

基　　金：陕西省自然科学基金项目:两阶段不确定规划问题中的信息价值研究(2013JM1003)资助

摘　　要：供应链竞争力变量因素多、信息量少、数据收集困难,造成其难以被准确评价。针对该问题构建了一个新的供应链评价指标体系,提出了一种新的供应链竞争力评价方法。它利用蜂群算法全局优化能力强的优点,对支持向量机的控制参数进行有效优化,以此为基础,构建了ABC-SVM评价模型。实验结果表明,所提方法能够有效提高供应链竞争力的评价精度,对提高企业决策效率具有积极意义。Aiming at that the supply chain is difficult to accurately evaluate, it comes from more variable facters, less amout of information and the difficult data collection. This paper built a new evaluation index system of supply chain and proposed a new supply chain competitiveness evaluation method. It uses the advantages of global optimization ability of artificial bee colony algorithm to optimize the control parameters of support vector machine effectively, and on this basis, the ABC-SVM evaluation model is constructed. The experimental results show that the new proposed method can effectively improve the evaluation presision of the supply chain competitiveness, and has a positive meaning to improve business decision-making effctiveness.

关 键 词：供应链竞争力 支持向量机 人工蜂群算法 参数优化 评价模型 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]