基于变权和TOPSIS方法的灰色关联决策模型

Grey Relational Decision-making Model Based on Variable Weight and TOPSIS Method

为提高现行灰色关联模型决策结果的可靠性,将惩罚型变权方法引入到模型指标权重设定中,使各方案指标权重随指标状态值的变化而变化;同时借鉴TOPSIS方法的思想,分别考察各候选方案与正、负理想方案间的关联程度并予以集成;构建了基于变权和TOPSIS方法的灰色关联决策模型。将其应用于项目评标决策案例,通过与现行方法的对比分析,证明了该模型有助于优选出指标间较为均衡的方案,决策结果更为合理可靠;通过不同惩罚水平下结果的对比分析,表明该模型具有较强灵活性,可以适应不同的均衡决策要求。

In this paper,the punishing variable weight method is introduced into the grey relational decision-making model to improve the model reliability,allowing weights of indexes for each alternative vary with their state values.Then,a comprehensive relative index integrating grey relational grade with both the ideal and negative-ideal solution is established,creating in a grey relational decision-making model based on variable weight and TOPSIS method.Finally,a comparison with the existing methods through a case study on project bidding evaluation decision-making shows the method introduced in this paper is able to select well-balanced alternatives,leading to more reasonable and reliable decision-making results.A comparison of decisionmaking results at different punishing levels indicates the model proposed in this paper is more flexible,which is able to meet different demands of balanced decision-making.