图像模糊偏好关系的加性一致性分析

Xiaoyu Wu, Tingting Zheng, Weiwei Meng, Jung-Chang Liu
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引用次数: 1

摘要

图像模糊集是对直觉模糊集的一种推广,具有正隶属、中立隶属和负隶属的特征。以图像模糊数为元素的图像模糊偏好关系比直观模糊偏好关系更能表达决策者的综合偏好信息。本文将重点研究PFPR添加剂的一致性。首先,提出了一种新的评分函数,以获得稳定一致的评分值来对备选方案进行排序。然后,研究了PFPR与归一化图像模糊优先级权重向量的加性一致性。随后,提出了6个目标规划模型,分别从个人和群体pfpr中生成优先级。最后,给出了三个数值算例来说明该方法的灵活性和合理性。并通过与现有方法的比较,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Additive Consistency Analysis for Picture Fuzzy Preference Relation
As a generalization of intuitionistic fuzzy set, picture fuzzy set is characterized by positive membership, neutral membership and negative membership. The picture fuzzy preference relation (PFPR), whose elements are picture fuzzy numbers, is stronger than intuitionistic fuzzy preference relation in expressing comprehensive preference information of decision-makers. This paper will focus on the additive consistency of PFPR. Firstly, a novel score function is proposed to obtain stable and consistent score values for ranking the alternatives. Then, the additive consistency of PFPR and normalized picture fuzzy priority weight vectors are studied. Subsequently, six goal programming models are proposed to generate the priorities from individual and group PFPRs, respectively. Finally, three numerical examples are provided to illustrate the flexibility and rationality. What’s more, the effectiveness is verified by comparing it with some existing methods.
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