Bridging the gap between missing and inconsistent values in eliciting preference from pairwise comparison matrices
作者： Kun Chen , Gang Kou , J. Michael Tarn , Yan Song
DOI: 10.1007/S10479-015-1997-Z
关键词: Pairwise comparison 、 Algorithm 、 Theory of computation 、 Preference (economics) 、 Mathematical proof 、 Missing data 、 Mathematics 、 Data mining 、 Consistency (statistics) 、 Path (graph theory) 、 Logarithm
摘要: Missing values and inconsistency of pairwise comparison matrices (PCM) in AHP are tackled with different methods in extant studies. In this article, we prove that connecting path method (CPM), which is a well-known approach of estimating missing judgments, also guarantees minimal geometric consistency index, and only involves elementary connecting paths by unraveling its connection with logarithmic least square method. The formal proofs suggest that CPM alone is sufficient to fix both missing judgments and inconsistency of PCM …
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