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作 者:刘金培[1] 陈佩佩 陈华友[3] 王书玲 LIU Jinpei;CHEN Peipei;CHEN Huayou;WANG Shuling(School of Business, Anhui University, Hefei 230601, China;Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China;School of Mathematical Science, Anhui University, Hefei 230601, China;School of Computer Science and Engineering, Southeast University, Nanjing 211102, China)
机构地区:[1]安徽大学商学院,合肥230601 [2]中国科学院科技战略咨询研究院,北京100190 [3]安徽大学数学科学学院,合肥230601 [4]东南大学计算机科学与工程学院,南京211102
出 处:《系统工程理论与实践》2018年第4期950-959,共10页Systems Engineering-Theory & Practice
基 金:国家自然科学基金(71501002,71371011,61502003,71301001);安徽省自然科学基金(1508085QG149,1608085QF133);安徽省哲学和社科规划青年基金(AHSKQ2014D13,AHSKQ2016D13)~~
摘 要:针对区间加性语言偏好关系排序问题,提出一种基于交叉效率DEA和随机模拟的排序向量计算方法.首先,针对具有一致性的加性语言偏好关系,构建产出导向的DEA模型,分析其相对效率得分与排序向量之间的内在关联.其次,对不满足一致性的加性语言偏好关系,建立改进仁慈型语言偏好关系交叉效率DEA模型,并提出基于该模型的加性语言偏好关系的排序方法.最后,将构建的DEA模型与随机偏好分析相结合,提出区间加性语言偏好关系期望排序向量和可信度的Monte Carlo计算方法.算例分析表明,本文提出的方法能够有效避免信息损失,具有较好的可信度和适用性.For the ranking problem of interval additive linguistic preference relation, we propose a new method to calculate the priority vector based on cross efficiency DEA and stochastic simulation. Firstly, the output-oriented DEA model is constructed for the additive consistent preference relations, and the intrinsic correlation between the relative efficiency score and the ranking vector is analyzed. Secondly, we develop a revised benevolent cross-evaluation DEA model for the inconsistent additive linguistic pref- erence relation and a sorting method of additive linguistic preference relation is proposed based on this model. Finally, the proposed DEA model is combined with stochastic preference analysis, and a Monte Carlo calculation method for the expected priority vector and confidence of the interval additive linguistic preference relations is proposed. The numerical results show that the proposed method can effectively avoid the loss of information and has good reliability and applicability.
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