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The optimization ordering model for intuitionistic fuzzy preference relations with utility functions

机译:具有效用函数的直觉模糊偏好关系的优化排序模型

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摘要

Intuitionistic fuzzy sets describe information from the three aspects of membership degree, non-membership degree and hesitation degree, which has more practical significance when uncertainty pervades qualitative decision problems. In this paper, we investigate the problem of ranking intuitionistic fuzzy preference relations (IFPRs) based on various non-linear utility functions. First, we transform IFPRs into their isomorphic interval-value fuzzy preference relations (IVFPRs), and utilise non-linear utility functions, such as parabolic, S-shaped, and hyperbolic absolute risk aversion, to fit the true value of a decision-maker’s judgement. Ultimately, the optimization ordering models for the membership and non-membership of IVFPRs based on utility function are constructed, with objective function aiming at minimizing the distance deviation between the multiplicative consistency ideal judgment and the actual judgment, represented by utility function, subject to the decision-maker’s utility constraints. The proposed models ensure that more factual and optimal ranking of alternative is acquired, avoiding information distortion caused by the operations of intervals. Second, by introducing a non-Archimedean infinitesimal, we establish the optimization ordering model for IFPRs with the priority of utility or deviation, which realises the goal of prioritising solutions under multi-objective programming. Subsequently, we verify that a close connection exists between the ranking for membership and non-membership degree IVFPRs. Comparison analyses with existing approaches are summarized to demonstrate that the proposed models have advantage in dealing with group decision making problems with IFPRs.
机译:直觉模糊集从隶属度,非隶属度和犹豫度三个方面描述信息,当不确定性遍及定性决策问题时,具有更实际的意义。在本文中,我们研究了基于各种非线性效用函数对直觉模糊偏好关系(IFPR)进行排名的问题。首先,我们将IFPR转换为其同构的区间值模糊偏好关系(IVFPR),并利用非线性效用函数(例如抛物线型,S形和双曲线型绝对风险规避)来拟合决策者的真实价值。判断。最终,建立了基于效用函数的IVFPRs隶属关系和非隶属关系的优化排序模型,其目标函数旨在最小化乘用函数表示的乘性一致性理想判断与实际判断之间的距离偏差,服从于决策者的效用约束。提出的模型可确保获得更多的事实性和最佳替代方案排名,避免了区间操作导致的信息失真。其次,通过引入非阿基米德无穷小,我们建立了以效用或偏差为优先级的IFPR的优化排序模型,从而实现了在多目标规划下对解决方案进行优先排序的目标。随后,我们验证成员资格排名与非成员资格IVFPR之间存在紧密联系。总结了与现有方法的比较分析,以证明所提出的模型在处理IFPR的群体决策问题方面具有优势。

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