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Isomorphic multiplicative transitivity for intuitionistic and interval-valued fuzzy preference relations and its application in deriving their priority vectors

机译:直觉和区间值模糊偏好关系的同构乘法传递性及其在推导优先级向量中的应用

摘要

Intuitionistic fuzzy preference relations (IFPRs) are used to deal with hesitation while interval-valued fuzzy preference relations (IVFPRs) are for uncertainty in multi-criteria decision making (MCDM). This article aims to explore the isomorphic multiplicative transitivity for IFPRs and IVFPRs, which builds the substantial relationship between hesitation and uncertainty in MCDM. To do that, the definition of the multiplicative transitivity property of IFPRs is established by combining the multiplication of intuitionistic fuzzy sets and Tanino's multiplicative transitivity property of fuzzy preference relations (FPRs). It is proved to be isomorphic to the multiplicative transitivity of IVFPRs derived via Zadeh's Extension Principle. The use of the multiplicative transitivity isomorphism is twofold: (1) to discover the substantial relationship between IFPRs and IVFPRs, which will bridge the gap between hesitation and uncertainty in MCDM problems; and (2) to strengthen the soundness of the multiplicative transitivity property of IFPRs and IVFPRs by supporting each other with two different reliable sources, respectively. Furthermore, based on the existing isomorphism, the concept of multiplicative consistency for IFPRs is defined through a strict mathematical process, and it is proved to satisfy the following several desirable properties: weak--transitivity, max-max--transitivity, and center-division--transitivity. A multiplicative consistency based multi-objective programming (MOP) model is investigated to derive the priority vector from an IFPR. This model has the advantage of not losing information as the priority vector representation coincides with that of the input information, which was not the case with existing methods where crisp priority vectors were derived as a consequence of modelling transitivity just for the intuitionistic membership function and not for the intuitionistic non-membership function. Finally, a numerical example concerning green supply selection is given to validate the efficiency and practicality of the proposed multiplicative consistency MOP model.
机译:直觉模糊偏好关系(IFPRs)用于处理犹豫,而区间值模糊偏好关系(IVFPRs)用于多标准决策(MCDM)中的不确定性。本文旨在探讨IFPR和IVFPR的同构乘法传递性,从而在MCDM中建立犹豫与不确定性之间的实质关系。为此,通过将直觉模糊集的乘积与Tanino的模糊偏好关系(FPR)的乘积传递性相结合,建立了IFPR乘积传递性的定义。它被证明与通过Zadeh的扩展原理导出的IVFPR的乘法传递性同构。乘法传递性同构的使用是双重的:(1)发现IFPR和IVFPR之间的实质关系,这将弥合MCDM问题中犹豫与不确定性之间的鸿沟; (2)分别通过两个不同的可靠来源相互支持,以增强IFPR和IVFPR的乘法传递性的稳健性。此外,在现有同构的基础上,通过严格的数学过程定义了IFPR的乘性一致性的概念,并证明它满足以下几个理想的性质:弱-传递性,max-max-传递性和中心-传递性分裂-及物性。研究了基于乘性一致性的多目标规划(MOP)模型,以从IFPR导出优先级向量。该模型的优点是不会丢失信息,因为优先级向量表示与输入信息一致,而在现有方法中,情况并非如此,在现有方法中,仅对直觉隶属函数进行建模可传递性而得出了清晰的优先级向量,而不是直觉的非会员功能。最后,给出了一个有关绿色供应选择的数值例子,以验证所提出的乘性一致性MOP模型的效率和实用性。

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