基于偏好完备性的层次分析法的一个公理系统

IF 3.2 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Fang Liu , Lin-Tao Dai , Fei-Yang Cheng , Wei-Guo Zhang
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引用次数: 0

摘要

决策结果依赖于决策者(DM)对备选方案的偏好。完备性公理是偏好理论的一个基本假设。本文报道了偏好理论下的层次分析法(AHP)公理系统。首先,分析了层次分析法现有的公理基础。研究发现,Saaty的方法受到比较比率互反性质的严格数学直觉的限制。由不确定性引起的不确定性可能会由于互反性质的破坏而导致偏好的混淆。其次,根据偏好的完备性构造了比较比率的约束关系,并将其应用于层次分析法的公理体系中。第三,提出了成对比较矩阵的有序一致性和可接受有序一致性的概念。利用Spearman秩相关系数构建了测量序列一致性的指标,克服了现有指标的不足。讨论了排序方法,揭示了几何平均法适用于具有序一致性的pcm。结果表明,建立的层次分析法公理基础合理地嵌入了决策对象的偏好信息。研究结果有助于确定在不确定情况下如何通过考虑决策者的完全偏好来灵活地应用层次分析法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An axiom system of the analytic hierarchy process based on the completeness of preferences
Decision outcomes rely on the preferences of the decision maker (DM) over alternatives. The completeness axiom is a fundamental assumption of preference theory. This paper reports an axiom system of the analytic hierarchy process (AHP) under the theory of preferences. First, the existing axiomatic foundations of AHP are analyzed. It is found that the Saaty's one is limited by strict mathematical intuition for the reciprocal property of comparison ratios. The uncertainty-induced one could lead to the confusion of preferences owing to the breaking of reciprocal property. Second, the constrained relation of comparison ratios is constructed according to the completeness of preferences, which is used to form a novel axiom system of AHP. Third, the concepts of ordinal consistency and acceptable ordinal consistency are developed for pairwise comparison matrices (PCMs). The index of measuring ordinal consistency is constructed using Spearman rank correlation coefficient to overcome the shortcoming in the existing one. The prioritization method is discussed to reveal that the geometric mean method is suitable for PCMs with ordinal consistency. It is revealed that the developed axiomatic foundation of AHP reasonably embeds the preference information of DMs. The results help to identify how to flexibly apply AHP in practice by considering the complete preferences of DMs under uncertainty.
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来源期刊
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning 工程技术-计算机:人工智能
CiteScore
6.90
自引率
12.80%
发文量
170
审稿时长
67 days
期刊介绍: The International Journal of Approximate Reasoning is intended to serve as a forum for the treatment of imprecision and uncertainty in Artificial and Computational Intelligence, covering both the foundations of uncertainty theories, and the design of intelligent systems for scientific and engineering applications. It publishes high-quality research papers describing theoretical developments or innovative applications, as well as review articles on topics of general interest. Relevant topics include, but are not limited to, probabilistic reasoning and Bayesian networks, imprecise probabilities, random sets, belief functions (Dempster-Shafer theory), possibility theory, fuzzy sets, rough sets, decision theory, non-additive measures and integrals, qualitative reasoning about uncertainty, comparative probability orderings, game-theoretic probability, default reasoning, nonstandard logics, argumentation systems, inconsistency tolerant reasoning, elicitation techniques, philosophical foundations and psychological models of uncertain reasoning. Domains of application for uncertain reasoning systems include risk analysis and assessment, information retrieval and database design, information fusion, machine learning, data and web mining, computer vision, image and signal processing, intelligent data analysis, statistics, multi-agent systems, etc.
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