• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Decision sciences >Stochastic Judgments in the AHP: The Measurement of Rank Reversal Probabilities
【24h】

Stochastic Judgments in the AHP: The Measurement of Rank Reversal Probabilities

机译：AHP中的随机判断：等级反转概率的度量

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper presents a methodology for analyzing Analytic Hierarchy Process (AHP) rankings if the pairwise preference judgments are uncertain (stochastic). If the relative preference statements are represented by judgment intervals, rather than single values, then the rankings resulting from a traditional (deterministic) AHP analysis based on single judgment values may be reversed, and therefore incorrect. In the presence of stochastic judgments, the traditional AHP rankings may be stable or unstable, depending on the nature of the uncertainty.We develop multivariate statistical techniques to obtain both point estimates and confidence intervals of the rank reversal probabilities, and show how simulation experiments can be used as an effective and accurate tool for analyzing the stability of the preference rankings under uncertainty. If the rank reversal probability is low, then the rankings are stable and the decision maker can be confident that the AHP ranking is correct. However, if the likelihood of rank reversal is high, then the decision maker should interpret the AHP rankings cautiously, as there is a subtantial probability that these rankings are incorrect. High rank reversal probabilities indicate a need for exploring alternative problem formulations and methods of analysis.The information about the extent to which the ranking of the alternatives is sensitive to the stochastic nature of the pairwise judgments should be valuable information into the decision-making process, much like variability and confidence intervals are crucial tools for statistical inference. We provide simulation experiments and numerical examples to evaluate our method.Our analysis of rank reversal due to stochastic judgments is not related to previous research on rank reversal that focuses on mathematical properties inherent to the AHP methodology, for instance, the occurrence of rank reversal if a new alternative is added or an existing one is deleted.
机译：如果成对的偏好判断是不确定的（随机的），则本文提出了一种用于分析层次结构等级（AHP）排名的方法。如果相对偏好陈述是由判断间隔而不是单个值表示的，则基于单个判断值的传统（确定性）AHP分析得出的排名可能会被颠倒，因此是不正确的。在存在随机判断的情况下，根据不确定性的性质，传统的AHP排序可能是稳定的也可能是不稳定的。我们开发了多元统计技术来获取秩估计概率的点估计和置信区间，并展示了仿真实验如何能够可以用作分析不确定性下偏好排名稳定性的有效且准确的工具。如果排名逆转概率较低，则排名是稳定的，决策者可以确信AHP排名是正确的。但是，如果排名逆转的可能性很高，则决策者应谨慎解释AHP排名，因为这些排名有很大的可能性是不正确的。高等级逆转概率表明有必要探索替代问题的表述和分析方法。关于替代方案的排名对成对判断的随机性敏感程度的信息应成为决策过程中的宝贵信息，就像变异性和置信区间是统计推断的关键工具。我们提供了仿真实验和数值示例来评估我们的方法。由于随机判断而导致的排名反转的分析与先前针对AHP方法固有的数学属性的排名反转的研究无关，例如，如果添加了新的替代方案或删除了现有的替代方案。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号