在基于Vague集的多准则决策过程中, 评分函数是影响评价结果的决定性因素之一. 现有评分函数对Vague集未知信息的处理都不恰当,
有的忽略了未知信息对评价结果的影响, 有的则夸大了未知信息的影响, 所以都存在评价结果与人们直觉判断不符的问题. 在总结和整
合前人工作的基础上, 提出了一种新的评分函数, 可根据未知信息的多少决定其对评价结果的影响程度, 有效地解决了评价结果与直觉判断
不符的问题, 并据此提出了一种计算Vague集相似度的新方法.

The scoring function is a crucial part in multi-criteria decision-making based on vague set. However, the evaluation results of existing scoring functions are not always consistent with our intuitive judgment because of the unknown information of vague set. Some scoring functions trend to ignore the
unknown information's influence on evaluation, and others trend to magnify the influence. This paper integrates two principal existing scoring functions and introduces a new function in which the unknown information's influence is determined by the amount of unknown information. This function solves the inconsistency of evaluation result and intuitive judgment. A new similarity measure of vague sets is presented based on the scoring function.