Significance of the order of pair-wise comparisons in Analytic Hierarchy Process: an experimental study

IF 1.9 Q3 MANAGEMENT
Oleh Andriichuk, Sergii Kadenko, Vitaliy Tsyganok
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引用次数: 0

Abstract

The article describes an approach, ensuring higher credibility of expert estimation results, based on specific order of pair-wise comparisons. The order of pair-wise comparisons is, in its turn, based on the distance between estimated objects in the ranking. According to the suggested approach (and some human psychophysiological features), the most ordinally distant objects should be compared before ordinally closer ones. In order to empirically confirm this assumption, a special experiment involving real experts has been conducted. The results of the experiment indicate that if objects are presented to the expert for comparison in the suggested order, then in the majority of cases relative weights of objects, obtained using eigenvector method, most adequately reflect this expert's priorities. Moreover, pair-wise comparison matrices constructed using the suggested comparison order tend to be slightly more consistent. The suggested approach to re-ordering of pair-wise comparisons can be applied as part of the AHP algorithm in weakly structured subject domains, influenced by multiple intangible criteria. It also provides conceptual basis for reduction of the number of pair-wise comparisons, required to obtain credible results, in AHP without loss or distortion of expert data. It can also be used for modification of combinatorial pair-wise comparison aggregation method, based on spanning tree enumeration. And, finally, it will improve the overall multi-criteria decision-making process in diverse subject domains, characterized by high uncertainty levels.

层次分析法中成对比较顺序的重要性:一项实验研究
文章介绍了一种方法,该方法基于成对比较的特定顺序,确保专家估算结果具有更高的可信度。成对比较的顺序又基于排序中估计对象之间的距离。根据建议的方法(以及人类的一些心理生理特征),应先比较顺序上最远的对象,然后再比较顺序上较近的对象。为了从经验上证实这一假设,我们进行了一项由真实专家参与的特别实验。实验结果表明,如果按照建议的顺序将物体呈现给专家进行比较,那么在大多数情况下,用特征向量法得出的物体相对权重能最充分地反映专家的优先顺序。此外,使用建议的比较顺序构建的成对比较矩阵往往略微更加一致。建议的成对比较重排序方法可作为 AHP 算法的一部分,应用于受多种无形标准影响的弱结构学科领域。它还为减少成对比较的数量提供了概念基础,在 AHP 中,成对比较是获得可信结果的必要条件,而不会损失或扭曲专家数据。它还可用于修改基于生成树枚举的组合式成对比较汇总方法。最后,它还能改进以高度不确定性为特征的不同主题领域的整体多标准决策过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.70
自引率
10.00%
发文量
14
期刊介绍: The Journal of Multi-Criteria Decision Analysis was launched in 1992, and from the outset has aimed to be the repository of choice for papers covering all aspects of MCDA/MCDM. The journal provides an international forum for the presentation and discussion of all aspects of research, application and evaluation of multi-criteria decision analysis, and publishes material from a variety of disciplines and all schools of thought. Papers addressing mathematical, theoretical, and behavioural aspects are welcome, as are case studies, applications and evaluation of techniques and methodologies.
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