摘要
针对具有多粒度不确定语言评价信息的多属性群决策问题,提出了一种基于区间二元语义信息处理和矢量相似度的群决策方法,弥补了基于距离测度的决策方法易造成信息混淆的不足。该方法首先使用二元语义转换函数对多粒度区间语言评价信息进行一致化处理;然后通过建立使备选方案对正理想解相似度最大、负理想解相似度最小的最优化模型来获得相应的属性权重;最后利用区间二元语义的集结算子对评价信息进行加权集成,并通过优序数排序法实现对各方案的排序。实例分析说明了该方法的可行性和有效性。
Based on interval two-tuple linguistic information and similarity of vector,a new method was proposed for multiple attribute group decision-making problems with multi-granularity uncertain linguistic information.It hopes to supplement the insufficiency of the method based on distance measure.Firstly,the multi-granularity linguistic information is uniformed using a two-tuple linguistic transformation function.Then,an optimization model,which aims to maximize the similarity degree of the alternatives to the positive ideal solution and minimize that to the negative ideal solution,is established,and then the attribute weights can be determined.The interval two-tuple aggregation operator is utilized to aggregate the linguistic assessment information corresponding to each alternative,and through the optimal ordinal ranking method,the alternatives can be ranked.An example was given to demonstrate the feasibility and efficiency of the proposed method.
出处
《计算机科学》
CSCD
北大核心
2016年第3期262-265,295,共5页
Computer Science
基金
国家自然科学基金项目(71171199)资助
关键词
群决策
多粒度
矢量相似度
区间二元语义
优序数
Group decision making
Multi-granularity
Similarity of vector
Interval two-tuple linguistic information
Optimal ordinal ranking
