摘要
将决策者风险偏好与属性约简算法应用到具有大量属性的决策问题,提出先对决策者分类再进行决策的策略.根据决策者的风险偏好特征将其分为风险规避型、风险中立型、风险偏好型,针对不同类型的决策者分别采取相应的算法,提取有效属性并利用有效属性进行决策;针对不同风险偏好的决策者,提出相应的风险偏好预期规则;提出基于优势关系辨析矩阵的属性赋权算法及基于属性值优势度矩阵的进行信息融合与排序算法;最后通过属性值为实数与区间数的两个实际案例表明该算法的科学合理性.
Appling the method of risk preferences and attribute reduction to large decision tables with many at- tributes, respectively, a new strategy is proposed that first classifies decision makers （DMs） and then makes decisions. First, the DMs are classifed into risk-aversion, risk-neutral, and risk-appetite types, then different methods are used to find out the useful criteria corresponding to the different types of DMs, only the useful cri- teria are used to make decisions. Second, three new risk preference assumptions are established according to the risk preferences of the decision makers. Third, a new method based on advantageous discernibility matrix is proposed to obtain attribute weights. Then, a new method, based on weighted combinatorial advantage val- ues （WCAV） for different risk preference decision makers, for information integration and alternative ranking is introduced. Finally, two real examples with numerical and interval value attribute values are presented to demonstrate the new method, respectively.
出处
《管理科学学报》
CSSCI
北大核心
2013年第8期68-79,共12页
Journal of Management Sciences in China
基金
国家社会科学基金重大招标资助项目(10zd&014)
国家自然科学基金资助项目(71002046
71071076
71071077
71171112)
国家科学技术学术著作出版基金资助项目(10td128)
南京理工大学青年教师科研基金资助项目(AE88370)
关键词
多属性决策
风险偏好
属性约简
优势关系
辨析矩阵
属性赋权
multi-attribute decisionmaking
risk preferences
attribute reduction
advantage relation
dis-cernibility matrix
obtain criteria weight
