Multi-Criteria Group Decision-Making Method Based on an Improved Single-Valued Neutrosophic Hamacher Weighted Average Operator and Grey Relational Analysis

This paper proposes a multi-criteria decision-making (MCGDM) method based on the improved single-valued neutrosophic Hamacher weighted averaging (ISNHWA) operator and grey relational analysis (GRA) to overcome the limitations of present methods based on aggregation operators. First, the limitations of several existing single-valued neutrosophic weighted averaging aggregation operators (i.e. , the single-valued neutrosophic weighted averaging, single-valued neutrosophic weighted algebraic averaging, single-valued neutrosophic weighted Einstein averaging, single-valued neutrosophic Frank weighted averaging, and single-valued neutrosophic Hamacher weighted averaging operators), which can produce some indeterminate terms in the aggregation process, are discussed. Second, an ISNHWA operator was developed to overcome the limitations of existing operators. Third, the properties of the proposed operator, including idempotency, boundedness, monotonicity, and commutativity, were analyzed. Application examples confirmed that the ISNHWA operator and the proposed MCGDM method are rational and effective. The proposed improved ISNHWA operator and MCGDM method can overcome the indeterminate results in some special cases in existing single-valued neutrosophic weighted averaging aggregation operators and MCGDM methods.

MCDM technique using single-valued neutrosophic trigonometric weighted aggregation operators

Motivated based on the trigonometric t-norm and t-conorm,the aims of this article are to present the trigonometric t-norm and t-conorm operational laws of SvNNs and then to propose the SvNN trigonometric weighted average and geometric aggregation operators for the modelling of a multiple criteria decision making(MCDM)technique in an inconsistent and indeterminate circumstance.To realize the aims,this paper first proposes the trigonometric t-norm and t-conorm operational laws of SvNNs,which contain the hybrid operations of the tangent and arctangent functions and the cotangent and inverse cotangent functions,and presents the SvNN trigonometric weighted average and geometric operators and their properties.Next,an MCDM technique is proposed in view of the presented two aggregation operators in the circumstance of SvNNs.In the end,an actual case of the choice issue of slope treatment schemes is provided to indicate the practicability and effectivity of the proposed MCDM technique.

基于单值中智VIKOR法的供应商优选模型

针对属性权重未知的供应商优选问题,提出一种基于单值中智VIKOR法的供应商优选模型。首先通过语言变量确定了决策专家和属性指标的权重;接着利用单值中智加权平均算子把所有专家给出的中智决策矩阵进行集结,构建综合中智决策矩阵;然后通过将VIKOR法扩展到单值中智环境下,得到备选供应商的折中最佳方案。最后通过仿真实例说明了模型的有效性和实用性,并结合灵敏性测试,验证了该模型的灵活性。

Human Immunodeficiency Virus (HIV) infection model based on triangular neutrosophic cubic hesitant fuzzy number

In this paper,we define the basic concept of triangular neutrosophic cubic hesitant fuzzy number and their properties.We develop a triangular neutrosophic cubic hesitant fuzzy ordered weighted arithmetic averaging (TNCIIFOWAA) operator and a triangular neu-trosophic cubic hesitant fuzzy ordered weighted geometric averaging (TNCIIFOWGA) operator to aggregate triangular neutrosophic cubic hesitant fuzzy number (TNCHFN) information and investigate their properties.Furthermore,a multiple attribute decision-making method based on the TNCHFOWAA operator and triangular neutrosophic cubic hesitant fuzzy ordered weighted geometric (TNCHFOWG) operator and the score function of TNCHFN is established under a TNCHFN environment.Finally,an illustrative example of investment alternatives is given to demonstrate the application and effec-tiveness of the developed approach.

社交网络环境下基于单值中智信息的大规模群决策方法

考虑到单值中智集具有全面且准确描述不确定信息的优势,文章提出了社交网络环境下基于单值中智信息的大规模群决策方法.首先,结合Louvain算法对社交网络进行分区,并确定分区团体中各决策者权重以及分区团体在整个社交网络中的权重.其次,提出改进的单值中智加权平均算子与改进的单值中智有序加权平均算子,并探讨算子的合理性以及相关性质.结合所提算子,对分区团体中各决策者的偏好信息以及整个网络中决策者的偏好信息进行集结.再次,采用单值中智距离测度检测分区团体中决策者的一致性水平,并利用改进的单值中智加权平均算子与单值中智数比较方法对候选方案进行排序.最后,结合中国某海外矿产投资项目选择案例验证所提方法的可行性与有效性,并通过灵敏度分析与比较分析证明所提方法的优越性.