摘要
就指标权重未知,且对方案有偏好的vague集多指标决策问题,提出了通过使决策者的主观偏好值与属性值的相离度最小来建立最优化模型,从而获得指标的权重.通过将vague值转化为模糊值来建立模糊值矩阵,由模糊值矩阵按各指标对应值的大小对方案进行排序,形成多个线性序,进而由线性序来构造模糊优先矩阵,对其进行截割,得到最优方案.最后通过一个实例说明此方法的具体决策过程.
In the light of the uncertain multicriteria decision - making problems with preference information on alternatives,this paper presents the optimization model by making deviation degree of preference value to attribute value minimum.Then attribute weights are obtained.By transforming Vague sets into fuzzy sets,the fuzzy matrix can be gotten.The alternatives are ranked according to every columns of the fuzzy matrix from big to small .Then the fuzzy priority relation matrix is obtained.By cutting the fuzzy priority relation matrix,the best alternative can be obtained.At the last,a practical example demonstrates the decision-making process.
出处
《数学的实践与认识》
CSCD
北大核心
2010年第6期99-102,共4页
Mathematics in Practice and Theory
基金
国家自然科学基金(70671066)
关键词
多指标决策
VAGUE集
偏好
相离度
multicriteria decision making
vague sets
preference
deviation degree
