Decision Quality Using Ranked Attribute Weights
评估了三种基于排序权重的近似公式在选择最佳多属性方案时的效果，发现排序质心权重最准确，且能推广到部分信息场景，为决策者提供了简单有效的工具。
Three published approximation formulae for selecting the best multiattribute alternative based on rank-ordered weights are evaluated. All formulae are surprisingly efficacious in determining the best multiattribute alternative. Rank order centroid (ROC) weights are more accurate than the other rank-based formulae; furthermore, the ROC formula generalizes to incorporate both other forms of partial information about attribute weights and partial rank order information as well. Because a ROC-based analysis is so straightforward and efficacious, it provides an appropriate implementation tool.