发表机构
University of Trento; University of Perugia（特伦托大学; 佩鲁贾大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文建立成对比较矩阵与最优传输理论间的联系，提出基于Sinkhorn的一致性刻画、优先级排序方法及熵不一致性指标，并经分析与数值验证。
AI 中文摘要
本文通过最优传输的视角重新诠释成对比较理论。主要贡献在于建立了成对比较矩阵、双随机缩放与熵正则化传输问题之间的联系。利用Sinkhorn缩放，我们展示了如何在一个统一的最优传输框架内研究一致性、优先级推导及不一致性评估。作为这一联系的方法论成果，我们获得了对一致性的新刻画、基于Sinkhorn的优先级排序方法以及基于熵的不一致性指标。我们从分析和数值两方面研究了这些提议，并与文献中的既有方法进行了比较。
英文摘要
In this paper, we reinterpret pairwise comparison theory through the lens of optimal transport. The main contribution is the connection established between pairwise comparison matrices, doubly stochastic scaling, and entropy-regularized transport problems. Using Sinkhorn scaling, we show how consistency, priority derivation, and inconsistency assessment can be studied within a common optimal-transport framework. As methodological consequences of this connection, we obtain a new characterization of consistency, a Sinkhorn-based prioritization method, and an entropy-based inconsistency index. We study these proposals both analytically and numerically and compare them with established methods from the literature
