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Exploring Multicriteria Elicitation Model Based on Pairwise Comparisons: Building an Interactive Preference Adjustment Algorithm

机译:基于成对比较的探索多标准赋予模型:构建交互式偏好调整算法

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摘要

Pairwise comparisons have been applied to several real decision making problems. As a result, this method has been recognized as an effective decision making tool by practitioners, experts, and researchers. Although methods based on pairwise comparisons are widespread, decision making problems with many alternatives and criteria may be challenging. This paper presents the results of an experiment used to verify the influence of a high number of preferences comparisons in the inconsistency of the comparisons matrix and identifies the influence of consistencies and inconsistencies in the assessment of the decision-making process. The findings indicate that it is difficult to predict the influence of inconsistencies and that the priority vector may or may not be influenced by low levels of inconsistencies, with a consistency ratio of less than 0.1. Finally, this work presents an interactive preference adjustment algorithm with the aim of reducing the number of pairwise comparisons while capturing effective information from the decision maker to approximate the results of the problem to their preferences. The presented approach ensures the consistency of a comparisons matrix and significantly reduces the time that decision makers need to devote to the pairwise comparisons process. An example application of the interactive preference adjustment algorithm is included.
机译:成对比较已应用于几个真正的决策问题。因此,该方法被从业者,专家和研究人员被认为是有效的决策工具。虽然基于成对比较的方法是普遍的,但是决策具有许多替代品和标准的问题可能是具有挑战性的。本文提出了一种实验的结果,用于验证大量偏好比较在比较矩阵的不一致中的影响,并确定常量和不一致的影响在决策过程的评估中。结果表明,难以预测不一致的影响,并且优先载体可以或可能不会受到低水平的不一致的影响,稠度比为0.1。最后,该工作介绍了一个交互式偏好调整算法,目的是减少成对比较的数量,同时捕获决策者的有效信息,以将问题的结果近似于他们的偏好。呈现的方法确保了比较矩阵的一致性,并显着降低了决策者需要投入到成对比较过程的时间。包括交互式偏好调整算法的示例应用。

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