A New Multiple Attribute Decision Making Method Based on Preference and Projection Pursuit Clustering Model

摘要：

A new combination assigning weight approach based on decision makers preference and projection pursuit clustering model is proposed to overcome the shortages of subjective and objective assigning weight approaches. The multidimensional data are easily transformed into low dimensional space and the structural feature of multidimensional data can be revealed through applying projection pursuit clustering model in multiple attribute decision making problems. The optimum projection and the value of projection function can be obtained by the adaptive clustering differential evolution algorithm raised in this paper. The simulation results verify the validity and efficiency of this approach.

作者: KONG Xiangyong LI Ruoping GAO Liqun FENG Da

作者单位: School of Information Science and Engineering,Northeastern University,Shenyang 110004,P.R.China State Key Laboratory of Integrated Automation for Process Industries (Northeastern University)

会议类型: 国际会议

会议名称: The 30th Chinese Control Conference(第三十届中国控制会议)

会议地点: 烟台

会议语种:英文

页码: 1-5

在线出版日期: 2011-07-01（万方平台首次上网日期，不代表论文的发表时间）