Accessing Informational Importance Using Intuitionistic Fuzzy Entropy Measures

• Main Authors: Chia Hang Li, 李佳航
• Other Authors: T.Y. Chen
• Format: Others
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/10228714901450788932

碩士 === 長庚大學 === 企業管理研究所 === 96 === In Multiple Attribute Decision Making (MADM), it is important to properly assess the attribute weight, because different weight result would often cause entirely different decision result. Furthermore, after the IFS was applied to solve MADM problems, it causes our data and decision matrix get more complex and contain more uncertainty, and therefore it is relatively important to make sure of the credibility of data itself. However, there is little investigation on MADM with the credibility of data being explicitly taken into account in the past. In our research, we propose a new objective weight method by using IF entropy measures for MADM under intuitionistic fuzzy environment. We utilize the nature of IF entropy to assess the attribute weight based on the credibility of data. Moreover, there were many IF entropy measures which were originated with different theories, and we also investigate the differences among those varied measures. According to the experiment result, the differences undoubtedly exist among those measures. Even the measures which were originated from the same theory also contain variation among them. Besides, we also understand the number of attributes and alternatives would influence the degree of difference among those measures.