一种基于目标规划的AHP参数学习算法

为提高采用层次分析(AHP)算法辅助采购决策问题的准确性,针对用户的最终选择与模型推荐结果的不一致,该文采用目标规划方法对AHP模型参数权重进行学习。通过理论分析和实例说明了算法的可行性,并将算法初步应用于某摩托车电子商务平台供应商选择决策支持系统。这种基于目标规划的AHP参数学习算法可通过多次学习积累采购者的评价习惯,弥补行业性电子商务平台一般性决策支持工具的不足,也可以用于其它决策支持领域相近问题。

Goal programming-based AHP criteria weight learning algorithm

An analytic hierarchy process (AHP) model was developed for vendor selection in a vertical E-commerce environment. The accuracy of the AHP-assisted decisions was improved with a goal-programming algorithm which adjusted the AHP criteria weights. The algorithm learns from the differences between a user's choices and the recommendations that the AHP model generates and can learn a decision maker's evaluation habits by averaging multiple learning results. Therefore, the algorithm greatly enhances the effectiveness of the AHP model. The algorithm was applied in a vendor selection system for a motorcycle industry E-commerce platform. Besides vendor selection problems, the algorithm is also applicable to other decision-making problems as well.