有序分位加权集结算子及在激励评价中的应用

发布时间：2018-06-09 03:43

  本文选题：综合评价 + 激励评价　； 参考：《系统工程理论与实践》2017年02期

【摘要】：为在信息集结过程中体现指标值的相对发展水平,提出了一种新的集结方法,即有序分位加权集结算子.该算子尤其适用于激励评价问题,其主要特征是用分位数表示指标值的相对发展水平,并且在信息集结过程中融入了决策者不同程度的激励偏好.通过性质分析,发现该算子具有置换不变性、界值性和条件单调性等特征.进一步,以算例的方式分析了该算子在激励评价中的应用问题,发现该算子在信息集结中通过权重加和不等于1的方式能够放大或缩小集结值,从而凸显被评价对象之间的差异,实现激励的目的.
[Abstract]:In order to reflect the relative development level of the index value in the process of information aggregation, a new aggregation method, the ordered quantile weighted aggregation operator, is proposed. This operator is especially suitable for incentive evaluation problems. The main feature of the operator is that the relative development level of the index value is expressed by quantiles, and the decision makers' incentive preferences are incorporated in the process of information aggregation. By property analysis, it is found that the operator is permutation invariant, bounded value and conditional monotonicity. Furthermore, the application of the operator in incentive evaluation is analyzed by a numerical example. It is found that the operator can enlarge or reduce the aggregation value by adding the weight and not equal to 1 in the information aggregation. In order to highlight the difference between the object of evaluation, to achieve the purpose of motivation.
【作者单位】： 东北大学工商管理学院;东北大学东北评价中心;
【基金】：国家自然科学基金(71671031) 中国博士后科学基金(2015M570256)~~
【分类号】：C934
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本文编号：1998728