Some extensions of the precise consistency consensus matrix
Some extensions of the precise consistency consensus matrix
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DOI：
10.1016/j.dss.2015.04.005
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发表时间：
2015-06
期刊：
影响因子：
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通讯作者：
M. T. Escobar;J. Aguarón;J. Moreno‐Jiménez
中科院分区：
文献类型：
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作者：
M. T. Escobar;J. Aguarón;J. Moreno‐Jiménez
精确共识一致性矩阵(PCCM)是由Aguarón等人定义的一种AHP-GDM工具。[2]并在为决策者分配相同权重的当地背景下(单一标准)制定。使用行几何平均数作为优先排序程序，当不同决策者对其初始立场或判断的修改保证在给定不一致程度可接受的值范围内时，寻求不同决策者之间的共识。本文从两个方面对原算法进行了改进：(1)考虑了决策者权重不同的情况；(2)强化了算法设计中的一致性思想。这种决策工具的缺点之一是，有时不可能实现一个完整的矩阵。为了解决这一问题，我们提出了一个程序，用于获得一个完整的共同共识判断矩阵，或者至少一个具有得出优先级所需的最少条目数量的矩阵。最后，我们将PCCM的扩展与AHP-GDM中常用的两种传统方法(AIJ和AIP)所得到的结果进行了比较。为了做到这一点，我们使用了一套指标来衡量两种情况(加权和非加权决策者)和两种情况(完整和不完整的PCCM)相关的四种情况下群体成对矩阵的违反情况以及个人和群体立场之间的兼容性。
The Precise Consensus Consistency Matrix (PCCM) is an AHP-Group Decision Making (AHP-GDM) tool, defined by Aguarón et al. [2] and developed in a local context (a single criterion) in which the decision makers are assigned the same weights. Using the Row Geometric Mean as the prioritisation procedure, consensus is sought between the different decision makers when the modifications of their initial positions or judgements are guaranteed to be within the range of values accepted for a given inconsistency level. This paper upgrades the algorithm initially proposed for obtaining the PCCM in two ways: (i) it considers the case of different weights for the decision makers; and (ii) it strengthens the idea of consistency in the design of the algorithm. One of the drawbacks of this decisional tool is that it is sometimes impossible to achieve a complete matrix. To address this, we propose a procedure for attaining a complete common consensus judgement matrix or, at least, a matrix with the minimum number of entries that are required to derive the priorities. Finally, we compare the results obtained when applying the extensions of the PCCM with those obtained using the two traditional procedures (AIJ and AIP) usually employed in AHP-GDM. In order to do this, we use a set of indicators that measure the violations in consistency of the group pairwise matrices and the compatibility between the individuals and group positions in four cases associated with two scenarios (weighted and non-weighted decision makers) and two situations (complete and incomplete PCCMs).