Estimating the attribute weights through evidential reasoning and mathematical programming

被引:26
作者
Deng, MR [1 ]
Xu, WX
Yang, JB
机构
[1] Zhejiang Univ, Sch Management, Inst Decis & Optimisat, Hangzhou 310027, Peoples R China
[2] Chinese Acad Sci, Inst Policy & Management, Beijing 100080, Peoples R China
[3] Univ Manchester, Inst Sci & Technol, Manchester M60 1QD, Lancs, England
关键词
weight estimation; evidential reason; non-linear programming;
D O I
10.1142/S0219622004001124
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An approach for estimating attribute weight is proposed, which is addressed to the problem inverse to the aggregation assessment based on a hierarchy of attributes. Evidential reasoning framework is employed since the assessment on some basic attributes may be uncertain and incomplete. As a by-product, a simple formula for evidence combination for our special case is obtained. The weights are estimated based on the preference given by the decision-maker, and represented as intervals. The more abundant preference the decision-maker shows, the clearer the relation among the basic attributes.
引用
收藏
页码:419 / 428
页数:10
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