非均衡语言信息的计算方法及其在TOPSIS法中的应用

发布时间：2018-06-12 08:30

本文选题：非均衡语言集合 + 逼近理想解排序法　；参考：《控制与决策》2017年04期

【摘要】：大多用语言描述偏好的决策问题假设语言是均匀、对称分布的,然而有些问题需要采用非均衡语言.针对这一问题,提出一种基于符号化方法的语言计算模型.首先,构造一种基于基础语言集合的加权图,用图形中的点描述非均衡语言;然后,定义图形中任意两点间的曼哈顿距离公式,用于计算非均衡语言的距离;最后,将其用于逼近于理想值的排序方法(TOPSIS),并给出算例.所提出的方法不仅图像化非均衡语言,而且在解决TOPSIS问题时比欧氏距离测度更具优越性.
[Abstract]:Most decision problems that describe preference by language assume that the language is uniformly and symmetrically distributed. However, some problems require the use of disequilibrium language. To solve this problem, a language computing model based on symbolic method is proposed. First, a weighted graph based on the basic language set is constructed to describe the disequilibrium language with the points in the graph. Then, the Manhattan distance formula between any two points in the graph is defined to calculate the distance between the disequilibrium languages. The method is used to sort the ideal value, and an example is given. The proposed method is not only graphical disequilibrium language, but also superior to Euclidean distance measure in solving TOPSIS problem.
【作者单位】：南京信息工程大学经济管理学院;
【基金】：国家自然科学基金项目(71401078,71503134) 江苏高校哲学社会科学研究基金项目(2014SJB059) 江苏省社会科学基金项目(14EYD006)
【分类号】：C934

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