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摘要翻译：
本文提出了一种灰色区间关系TOPSIS决策方法，其中属性权重和属性值均由区间灰数给出。该方法不同于其它灰色关联决策的特点是，所有主客观权重均由区间灰数求取，并利用二维欧氏距离，根据灰色TOPSIS的相对贴近度、灰色关联的相对贴近度和灰色关联的相对隶属度进行决策。采用加权Borda法将三种方法的结果结合起来。算例表明了该方法的适用性。
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英文标题：
《Novel Grey Interval Weight Determining and Hybrid Grey Interval Relation
Method in Multiple Attribute Decision-Making》
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作者：
Gol Kim (Center of Natural Science, University of Sciences, Pyongyang,
DPR Korea)
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最新提交年份：
2012
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
This paper proposes a grey interval relation TOPSIS for the decision making in which all of the attribute weights and attribute values are given by the interval grey numbers. The feature of our method different from other grey relation decision-making is that all of the subjective and objective weights are obtained by interval grey number and that decisionmaking is performed based on the relative approach degree of grey TOPSIS, the relative approach degree of grey incidence and the relative membership degree of grey incidence using 2-dimensional Euclidean distance. The weighted Borda method is used for combining the results of three methods. An example shows the applicability of the proposed approach.
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PDF链接：
https://arxiv.org/pdf/1207.2592
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