摘要
针对属性权重和专家权重信息都完全未知的多属性群决策问题,提出了一类以直觉模糊软集为数据环境的群决策方法。通过提取理想点结合距离测度构建非线性规划模型来求解属性权重。利用得分函数进行矩阵变换,基于各对象的综合正、负理想值构造满意度,并根据总体满意度最大化原则构建规划模型确定专家权重。最后利用属性权重和专家权重对得分矩阵进行加权平均,计算各对象的综合得分,进而给出具体的多属性群决策过程,并实例验证了决策方法的可行性和合理性。
In order to deal with the multiple attribute group decision-making problems that the attribute and expert weights are all completely unknown,a new group decision-making method based on the data environment of intuitionistic fuzzy soft sets（IFSS）has been proposed.The attribute weights are determined based on a nonlinear programming model by using ideal point and distance.The matrices are transformed with score function,and a satisfaction degree is constructed based on every object＇s overall positive and negative ideal values,and the expert weights could be determined by constructing aprogramming model based on the maximizing the overall satisfaction degree principle.Finally,the overall scores are obtained through the weighted average for the score matrices by using attribute and expert weights,and then a specific decision-making process is given,and a case study is presented to verify the proposed method＇s feasibility and rationality.
出处
《模糊系统与数学》
CSCD
北大核心
2016年第6期125-132,共8页
Fuzzy Systems and Mathematics
基金
国家自然科学基金资助项目(71371011)
安徽省高校优秀青年人才支持计划重点项目(No.gxyqZD2016453)
安徽省高等学校省级自然科学研究重点项目(KJ2016A250)
安徽三联学院自然科学校级重点项目(kjzd2016001)
关键词
属性权重
专家权重
直觉模糊软集
多属性群决策
满意度
Attribute Weights
Expert Weights
IFSS
Multiple Attribute Group Decision-making
Satisfaction Degree
