个性化个体语义驱动的语言分布多属性群决策

Personalized Individual Semantics-driven Multi-attribute Group Decision-making under Linguistic Distribution Environment

实际群决策中,相同语言表达被不同决策者个性化理解称之为个性化个体语义。针对语言分布评价信息下的多属性群决策问题,提出一种基于个性化个体语义的多属性群决策方法。首先,集成专家个性化的属性权重和最佳-最差方法(best-worst method,BWM)模型中的一致性驱动思想构建优化模型,确定每个专家的个性化个体语义标度;然后,为有效集结个体意见形成群体意见,在群体共识和可信度双视角下构建多目标优化模型,用来确定差异化的专家权重。在此基础上,计算群体关于备选方案的综合评价值对方案排序择优;最后,通过一个在线评论多属性群决策的案例说明所提决策方法的有效性和合理性。

In actual group decision-making,the same linguistic expression was understood by different decision-makers individually,which was called personalized individual semantics.Aiming at the problem of multi-attribute group decision-making with linguistic distribution assessment information,a multi-attribute group decision-making method based on personalized individual semantics was proposed.Firstly,an optimization model was constructed by integrating the personalized attribute weights of experts and the consistency-driven ideas from the BWM(best-worst method)model to determine the personalized individual semantic scale of each expert.Secondly,in order to effectively aggregate individual opinion to form group opinions,a multi-objective optimization model was established to determine the differentiated expert weights from the dual perspectives of group consensus and credibility.Based on these,the alternatives were ranked and selected by calculating the comprehensive evaluation values of the alternatives for the group.Finally,the validity and rationality of the proposed decision-making method were illustrated by a case of multi-attribute group decision-making with online reviews.