基于新图模糊距离的EDAS决策方法及其应用

An EDAS decision making method and its application based on a novel picture fuzzy distance

研究决策信息为图模糊集的多属性决策问题。首先,针对现有图模糊距离的不足,定义了含参数的弃权度的分配,同时结合一致性概念提出了反映决策者风险偏好的图模糊距离,通过数值算例将新图模糊距离与现有图模糊距离进行比较分析,验证其优越性。其次,针对属性权重,采用博弈论组合赋权法对熵权法确定的客观权重和决策者给出的主观权重进行组合优化。在此基础上,将新图模糊距离拓展到一种离平均方案距离的决策方法(EDAS),并运用新图模糊距离计算各方案与平均方案的正、负距离加权和,进而得到综合得分。最后,通过算例来验证所提决策方法的适用性和有效性。灵敏度与对比分析结果表明:决策者可以依据自身风险偏好调整参数的取值来满足不同的决策需求;所提方法相较于其他现有决策方法更具一般性与灵活性,所得排序结果更加合理。

For multi-attribute decision-making problems with decision information as picture fuzzy,this paper firstly defines the assignment of the degree of refusal membership with parameters based on the limitations of existing picture fuzzy distances.It also proposes a picture fuzzy distance that reflects decision-makers’risk preferences by combining consistency concepts.Through a numerical example,the new picture fuzzy distance is compared and analyzed with existing picture fuzzy distances to verify its superiority.Secondly,for attribute weights,this paper adopts the combination weighting method of game theory to combine the objective weights determined by entropy weighting with the subjective weights given by decision-makers.On this basis,the new picture fuzzy distance is extended to evaluation based on distance from average solution(EDAS)method,and the weighted sum of positive and negative distances between each scheme and the average scheme is calculated using the new distance,resulting in comprehensive scores.Finally,numerical examples are used to verify the applicability and effectiveness of the proposed decision-making method.Sensitivity and comparative analysis results show that decision-makers can adjust the parameter values according to their risk preferences to meet different decision-making needs.The method is more general and flexible compared to other existing decision-making methods,and the ranking results are more reasonable.