摘要
针对传统模糊TOPSIS方法在决策指标权重、相对贴近度计算过程中模糊和不确定信息损失的问题,提出一种基于相对偏好关系分析的距离测度方法,并将其分别运用于决策指标离散程度计算和改进方案与正、负理想解间的距离测度中,提出了主客观相结合的熵值法和基于相对偏好关系分析的模糊TOPSIS改进模型。最后,通过某企业供应商选择的实例验证,并与传统模糊TOPSIS方法进行对比,验证了所提方法的可行性和有效性。
For the problem of vague and uncertain information loss in the process of calculating the criteria weights and relative closeness coefficient in traditional fuzzy TOPSIS approach,an distance measure method based on relative preference relation analysis was proposed,which was used to calculate the dispersion degree of criteria and the distance from the scheme to positive and negative ideal solution separately,then an extended entropy method combined subjective with objective approaches and an improved TOPSIS model based on relative preference relation analysis were proposed.Finally,an example of supplier selection and a comparison with traditional fuzzy TOPSIS approach were given out to demonstrate the feasibility and effectiveness of the proposed approach.
出处
《软件导刊》
2017年第12期4-8,共5页
Software Guide
基金
江苏省社会科学基金项目(15GLD001)
金陵科技学院人才引进项目(jit-rcyj-201404)
关键词
多属性群决策
TOPSIS
相对偏好关系
距离测度
熵值法
multi-attribute group decision-making
TOPSIS
relative preference relation
distance measure
entropy method
