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Deriving consistent pairwise comparison matrices in decision making methodologies based on linear programming method

机译:基于线性规划方法的决策方法中一致的成对比较矩阵的推导

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摘要

Pairwise comparison matrix (PCM) with crisp or fuzzy elements should satisfy consistency requirements when it is used in analytic hierarchy process (AHP) or in fuzzy AHP methodologies. An algorithm has been presented to obtain a new modified consistent PCM for the corresponding inconsistent original one. The algorithm sets a linear programming problem based on all of the constraints. To obtain the optimum eigenvector of the middle value of the new PCM, segment tree is used to gradually approach the greatest lower bound of distance with the original PCM. As to obtain the lower value and upper value of the new PCM, a theory is proposed to reduce adding uncertainty factors and could maximum maintain the similarity with original PCM. The experiments for crisp elements show that the proposed approach can preserve more the original information than references. The experiments for fuzzy elements show that our method can effectively reduce inconsistency and obtain suitable modified fuzzy PCMs.
机译:带有清晰或模糊元素的成对比较矩阵(PCM)在分析层次过程(AHP)或模糊AHP方法中使用时,应满足一致性要求。已经提出了一种算法,用于为相应的不一致原始信号获得新的修改一致PCM。该算法根据所有约束条件设置线性规划问题。为了获得新PCM中间值的最佳特征向量,使用段树逐渐接近原始PCM的最大距离下限。为了获得新PCM的下限值和上限值,提出了减少附加不确定因素并最大程度地保持与原始PCM相似性的理论。脆性元素的实验表明,提出的方法比参考方法可以保留更多的原始信息。对模糊元素的实验表明,我们的方法可以有效地减少不一致性,并获得合适的改进模糊PCM。

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