基于三元联系数的不确定多属性决策方法

利用集对分析理论对不确定多属性决策方法进行了研究。给出了三元联系数的广义同一度以及候选方案与理想解之间的联系数距离的定义,提出了两种属性权重确知、且属性值为三元联系数的不确定多属性决策方法:广义同一度法和距离法。这两种方法均简洁直观,计算量小,易于在计算机上实现。最后,通过与已有方法的比较和实例分析,阐明了提出方法的有效性和优越性。

Uncertain multiple attribute decision making methods based on three-unit connection number

By referring to set pair analysis theory,methods for uncertain multiple attribute decision making are investigated.Generalized identity degree of three-unit connection number and distance of connection number for alternative and ideal alternative are defined.Two three-unit-connection-number-based methods are proposed for solving uncertain multiple attribute decision making problems,in which the attribute weights are completely known and the attribute values are three-unit connection numbers.Two methods are called generalized identity degree method and distance method,and they are straightforward,need less time in calculation and can be implemented on computer easily.Finally,they are compared with the existing methods,and two illustrative examples are provided to demonstrate their effectiveness and superiority.