TOPSIS方法在Vague集中的应用

Technique for Order Preference by Similarity to Ideal Solution(TOPSIS) Applied in Vague Sets

摘要: 研究属性值和权重皆为Vague值形式的逼近理想解的排序方法(TOPSIS).根据Vague集的加法和乘法对属性值加权;根据记分函数确定理想解和负理想解;定义Vague集上的Hausdorff测度,据此度量各方案与理想解和负理想解的距离,在此基础上提出了属性值和权重同时表示赞成度和反对度的Vague集TOPSIS方法,并通过实际算例验证该方法的有效性.

Abstract: Technique for order preference by similarity to ideal solution(TOPSIS),whose attribute value and weight are Vague sets,is brought into Vague sets.Attribute value is weighted according to addition and multiplication of Vague sets.Positive and negative ideal solutions are based on Score function.The distance of both positive and negative metrics is defined the Hausdorff metrics based on Vague sets,thus developing the TOPSIS methods based on Vague sets.It is finally verified effectively by a case.