基于联系数贴近度的区间数多属性决策方法

利用集对分析和联系数学理论对区间数多属性决策方法进行了研究.首先给出了联系数贴近度的定义和性质;然后在将区间数决策矩阵转化为联系数决策矩阵的基础上,依据传统的逼近理想解的排序方法(TOPSIS)的基本思路,基于联系数贴近度提出了一种区间数多属性决策新方法.该方法简洁直观,易于计算,无需对区间数进行排序;最后,通过算例表明了它的有效性和实用性.

Connection-number-similarity-measure-based Method for Multiple Attribute Decision Making with Interval Numbers

Referring to set pair analysis and connection mathematics theory,methods for multiple attribute decision making with interval numbers are investigated.Firstly,the connection number similarity measure is defined and its quality is given.By transforming interval numbers decision matrix into connection numbers decision matrix,using the traditional technique for order preference by similarity to ideal solution(TOPSIS),a connection-number-similarity-measure-based method for multiple attribute decision making with interval numbers is proposed.This method is straightforward and can be performed on computer easily.It can avoid comparing and ranking interval numbers.Finally,an illustrative example is also given to demonstrate the feasibility and practicability of the proposed method.