首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Optimal Inconsistency Repairing of Pairwise Comparison Matrices Using Integrated Linear Programming and Eigenvector Methods
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Optimal Inconsistency Repairing of Pairwise Comparison Matrices Using Integrated Linear Programming and Eigenvector Methods

机译:使用集成线性规划和特征向量法的成对比较矩阵最优不一致性修复

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Satisfying consistency requirements of pairwise comparison matrix (PCM) is a critical step in decision making methodologies. An algorithm has been proposed to find a new modified consistent PCM in which it can replace the original inconsistent PCM in analytic hierarchy process (AHP) or in fuzzy AHP. This paper defines the modified consistent PCM by the original inconsistent PCM and an adjustable consistent PCM combined. The algorithm adopts asegment treeto gradually approach the greatest lower bound of the distance with the original PCM to obtain the middle value of an adjustable PCM. It also proposes a theorem to obtain the lower value and the upper value of an adjustable PCM based on two constraints. The experiments for crisp elements show that the proposed approach can preserve more of the original information than previous works of the same consistent value. The convergence rate of our algorithm is significantly faster than previous works with respect to different parameters. The experiments for fuzzy elements show that our method could obtain suitable modified fuzzy PCMs.
机译:满足成对比较矩阵(PCM)的一致性要求是决策方法中的关键步骤。提出了一种算法,用于寻找新的修改后的一致性PCM,在该算法中它可以代替层次分析法(AHP)或模糊AHP中的原始不一致PCM。本文通过原始的不一致PCM和可调整的一致PCM的组合定义了修改后的一致PCM。该算法采用细分树,逐渐接近原始PCM的最大距离下限,以获得可调PCM的中间值。它还提出了一个定理,基于两个约束条件来获得可调PCM的下限值和上限值。脆性元素的实验表明,与具有相同一致性值的先前工作相比,所提出的方法可以保留更多的原始信息。对于不同的参数,我们的算法的收敛速度明显快于先前的工作。对模糊元素的实验表明,我们的方法可以获得合适的改进的模糊PCM。

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