基于改进蚁群算法的聚类分析及其在HRM中的应用  

Clustering problem based on improved ant colony algorithm and its application in HRM system

作　　者：翁怀荣[1] 张洪伟[1] 钟响[1] 陈维静[1] 

机构地区：[1]四川大学计算机学院,四川成都610064

出　　处：《计算机应用》2005年第8期1908-1912,共5页journal of Computer Applications

摘　　要：提出了一种基于改进蚁群算法(IACA)的员工绩效评估聚类分析模型。IACA算法是在基本蚁群算法的基础上引入随机扰动和感觉知觉特征,蚂蚁每次搜索完成后更新每条路径上的信息素浓度,最终选择信息素浓度最大的路径。本模型采用ASP和SQLServer2000数据库实现,并成功运用于国内一家大型乳业集团的HRM系统中,为该企业的员工绩效评估提供了一个新的方案。An employee performance evaluation clustering model, which based on Improved Ant Colony Algorithm, was put forward. Improved ant colony algorithm was based on ant colony algorithm and inducted random disturbing and sentience characters. The incretion in each path would be renewed in each searching time. Finally, the path which had the most incretion would be selected as the result. The realization of the model had been successfully used in the Human Resource Management of a dairy-industry company and introduced a new way in employee performance evaluation with the use of Active Server Pages and SQL Server 2000.

关 键 词：改进蚁群算法 聚类分析 绩效评估 

分 类 号：TP311.31[自动化与计算机技术—计算机软件与理论]