SITUATIONAL ME-LOWA AGGREGATION MODEL FOR EVALUATING THE BEST MAIN BATTLE TANK

摘要：

OWA (Ordered Weighted Averaging) operators have been extensively adopted to handle MCDM problems.However, previous operators are usually independent of their situations and cannot reflect change in situations.Besides, the evaluated data with linguistic preferences should be aggregated with feasible operators.To resolve above problems, a linguistic MCDM aggregation model with situational ME-LOWA operators is proposed in this study.The proposed model is applied to evaluate the best main battle tank, and experimental results indicate that the proposed model can deal the situational group MCDM problems with linguistic preferences.

关键词： Aggregation operators OWA operators ME-LOWA operators Information fusion Multiple criteria evaluation

作者: JING-RONG CHANG SHU-YING LIAO CHING-HSUE CHENG

作者单位: Department of Information Management, Chaoyang University of Technology, 168, Jifong East Road, Wufo Department of Information Management, National Yunlin University of Science and Technology 123, sect

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 1866-1870

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）