论文部分内容阅读
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。
In order to improve the accuracy of AHP (Assisted Analytical Hierarchy Process) decision-making, aiming at the discrepancy between the final choice of the user and the recommended result of the model, this paper adopts the target programming method to study the parameter weight of the AHP model. The feasibility of the algorithm is illustrated through theoretical analysis and examples, and the algorithm is initially applied to the supplier selection decision support system of a motorcycle e-commerce platform. The goal-based AHP parameter learning algorithm can accumulate buyer’s evaluation habits through multiple learning, make up for the lack of general decision support tools for industry e-commerce platform, and can also be used for similar issues in other decision support areas.