摘要
针对一类评价信息不完全且属性值由精确数、语言评价值等定量、定性形式构成的混合型不完全信息多属性群决策问题,提出了一种基于直觉模糊集和证据理论的决策方法。首先定义了转换函数将不同类型属性值一致转换为更符合决策实际的直觉模糊数,接着根据信息熵原理利用直觉模糊数中的犹豫度确定专家客观权重,随后应用证据理论集结含有信息缺失的评价值,并构造了一可能度比较公式用于集结后方案排序。该法解决了决策问题中易出现的信息残缺和混合型信息等情况,具有更强的实用性。最后的实例分析证明了该方法的科学性、有效性。
A new decision making approach is proposed for multi-attribute group decision making problem with incomplete hybrid assessment information. First, a conversion function is defined to transfer multifarious assessment information into intuitionistic fuzzy numbers . Then, based on the theory of information entropy, expert＇s objection weight is judged by his hesitating degree. The D-S theory is used to deal with incomplete assessment information, and a possibility degree formula is conceived to rank alternatives. Finally, an example is given to show the feasibility and availability of the theory.
出处
《中国管理科学》
CSSCI
北大核心
2009年第4期126-132,共7页
Chinese Journal of Management Science
基金
国家自然科学基金重点项目(70631003)
国家"863"项目(2006AA04A126)
国家自然科学基金项目(70471046)
关键词
多属性群决策
不完全信息
直觉模糊集
信息熵
证据理论
multi-attribute group decision making
incomplete information
intuitionistic fuzzy sets
information entropy
Dempster-Shafer Theory
