基于概率不确定犹豫模糊偏好关系的决策模型

针对犹豫模糊信息在现实决策中难以准确和充分的提供决策者评价信息的问题,引入了概率不确定犹豫模糊偏好关系（PUHFPR）的概念,其能够有效处理概率不确定犹豫模糊元（PUHFE）中元素发生概率信息部分已知和完全未知的决策问题;给出了PUHFPR的期望加行一致性、满意加性期望一致性定义,并以偏差最小化为目标函数构建最优化模型确定PUHFPR元素的发生概率;建立基于一致性调整算法的概率不确定犹豫模糊偏决策模型,得到方案的排序权重向量,从而选择最佳的方案;通过遴选上市公司进行投资的实例说明决策模型的有效性。     

模糊偏好关系一致性改进算法及其决策应用

模糊偏好关系是处理决策问题的一种有效工具。针对模糊偏好关系,研究了加性一致性模糊偏好关系的若干判定条件,构造了满足加性一致性的特征模糊偏好关系,并提出一致性指数、满意加性一致性等概念。在此基础上,构建了不满足加性一致性模糊偏好关系的改进算法,论证了算法的收敛性,该算法使得改进后的模糊偏好关系具有满意一致性条件,进而使得决策者获得合理可靠的决策结果。最后建立了基于模糊偏好关系加性一致性的决策模型。实例分析说明提出的模糊偏好关系决策模型是可行和有效的。     

基于模糊最优化模型的供应商选择方法研究

供应商选择是供应链管理中的一个重要课题,其本质是一个决策问题。针对供应商的选择问题,首先基于最优化模型提出一种乘性一致模糊偏好关系的构建方法,并引入新的一致性指数用以衡量模糊偏好关系的一致性水平。在此基础上,建立了基于乘性一致性调整算法的供应商权重确定方法,该方法不仅保证调整后的模糊偏好关系满足满意一致性条件,而且使得决策者获得合理可靠的供应商权重向量。最后将提出的选择方法运用于经销商选择综合条件最优的供应商问题中。     

加型Pythagorean模糊偏好关系的多属性决策方法

考虑Pythagorean模糊偏好关系的多属性决策问题,提出了加性Pythagorean模糊偏好关系的多属性决策方法。基于加性一致性Pythagorean模糊偏好关系提出一种新的Pythagorean模糊权重确定模型。给出了可接受加性一致性Pythagorean模糊偏好关系的定义,并针对不满足可接受加性一致性的Pythagorean模糊偏好关系,提出一种加性一致性调整算法。给出基于Pythagorean模糊偏好关系加性一致性的多属性决策方法,并通过实例分析提出的新方法的可行性和合理性。     

直觉语义决策模型应用于区块链风险投资

为了全面且精确地表达和处理复杂风险投资决策问题中的评价信息,构建了直觉模糊语义决策模型,并将其应用于区块链风险投资过程。首先,给出了直觉模糊语义互补判断矩阵(IFLCJM)的加性一致性概念,并建立了加性一致性IFLCJM与规范化直觉模糊权重向量之间的转化关系;其次,构造最优化模型计算IFLCJM与其完全加性一致性IFLCJM之间的差距,并以此来衡量IFLCJM的一致性水平;最后,设计了基于一致性提升算法的直觉模糊语义决策模型,并将其应用于区块链风险投资问题,结果验证了模型的合理性和可靠性。     

基于模糊群决策算法的高性能数据库优选

模糊群决策的两个主要问题包括完全一致模糊偏好关系(FPR)的构造和专家共识水平的提升,因此,构建了基于乘性一致性和共识调整模型的群决策算法,并将其运用于高性能数据库优选问题。首先,运用专家提供的FPR,设计一种完全乘性一致FPR的构造方法,进而引入同时衡量一致性和共识性的一致性-共识性指数;其次,提出基于最小调整成本策略的群共识调整模型,以共识调整总成本最小化为目标函数建立最优化模型,进而得到每个专家的最优调整参数和共识阈值下界;最后,构建一种具有收敛性的模糊群决策算法。通过高性能数据库产品的优选实验表明,所构建的群决策算法在成本和效率方面更为有效。     

基于粒计算的犹豫模糊多准则决策方法*

提出基于粒计算的犹豫模糊多准则决策方法.给出各个准则下对应的犹豫模糊集中犹豫模糊元的大于可能度定义,并构造相应准则下的加性一致的模糊偏好矩阵.根据各准则的模糊偏好矩阵对应的预序熵及预序粒结构相似度确定属性的权重,对各个准则下模糊偏好矩阵的排序向量加权平均得到最终的排序向量.文中方法以评价数据序信息量及准则序与整体之间的关系确定准则权重,通过计算加权两两比较下的排序向量得到最终的排序决策结果.最后运用实例验证算法的有效性及可行性.     

基于模糊语言偏好关系一致性改进的决策方法

针对决策者提供的偏好信息为语言标量的决策问题,首先引入了语言偏好关系的有序一致性和加性一致性的定义,研究了语言偏好关系加性一致性的判定方法,构建了满足加性一致性的诱导语言偏好关系,提出一致性指数和满意一致性的概念;然后建立了基于语言偏好关系一致性改进的决策算法,并证明了算法的收敛性,同时通过该算法改进后的语言偏好关系满足满意一致性条件。最后通过数据库系统的选择实例说明提出的决策算法是合理的和有效的。     

犹豫模糊群共识实现算法及其数据系统优选

针对犹豫模糊偏好关系（HFPR）可以在复杂的管理环境下全面描述专家的犹豫评价信息的优势,基于HFPR构建了一种犹豫模糊群共识实现算法,并将其应用于银行数据系统的选购过程中。引入一种新的一致性指数方法来衡量个体HFPR的一致性水平;为了提升群体专家对决策结果的满意度,设计了一种犹豫模糊群共识实现算法,该算法能够在群体HFPR达到共识水平的情况下保证个体HFPR仍然具有满意一致性;通过银行数据系统的选购实例和对比分析实验说明了提出的方法的实用性和有效性。     

属性权重未知情况下犹豫模糊多属性决策方法

针对属性权重未知的犹豫模糊多属性决策,利用犹豫模糊元边界的确定性与边界内隶属度的犹豫性,把犹豫模糊元转换成集对分析中的三元联系数;再根据三元联系数的势函数和属性离差最大法确定属性权重,基此建立属性权重未知条件下的基于三元联系数的犹豫模糊多属性决策模型,利用模型中不同犹豫强度对备选方案进行排序。实例计算和对比分析结果表明,新模型不仅包含了其他模型得到的结果,还提供了更多潜在的排序方案信息,由此形成的有条件决策,是犹豫模糊多属性决策不确定性本质属性的映照,与犹豫模糊多属性决策实际应用情况吻合。     

Multi-criteria group decision making with incomplete hesitant fuzzy preference relations

In order to simulate the hesitancy and uncertainty associated with impression or vagueness, a decision maker may give her/his judgments by means of hesitant fuzzy preference relations in the process of decision making. The study of their consistency becomes a very important aspect to avoid a misleading solution. This paper defines the concept of additive consistent hesitant fuzzy preference relations. The characterizations of additive consistent hesitant fuzzy preference relations are studied in detail. Owing to the limitations of the experts’ professional knowledge and experience, the provided preferences in a hesitant fuzzy preference relation are usually incomplete. Consequently, this paper introduces the concepts of incomplete hesitant fuzzy preference relation, acceptable incomplete hesitant fuzzy preference relation, and additive consistent incomplete hesitant fuzzy preference relation. Then, two estimation procedures are developed to estimate the missing information in an expert's incomplete hesitant fuzzy preference relation. The first procedure is used to construct an additive consistent hesitant fuzzy preference relation from the lowest possible number, (n − 1), of pairwise comparisons. The second one is designed for the estimation of missing elements of the acceptable incomplete hesitant fuzzy preference relations with more known judgments. Moreover, an algorithm is given to solve the multi-criteria group decision making problem with incomplete hesitant fuzzy preference relations. Finally, a numerical example is provided to illustrate the solution processes of the developed algorithm and to verify its effectiveness and practicality.     

A new procedure for hesitant multiplicative preference relations

Hesitant information is powerful and flexible to denote decision maker's judgments. Hesitant multiplicative preference relations (HMPRs) own the advantages of preference relations and hesitant fuzzy sets that permit the decision makers (DMs) to compare objects by using several values. Just as other types of preference relations, how to derive the priority weight vector is a crucial step. According to the principle of the consistency concept for multiplicative preference relations, this paper first introduces a new consistency concept for HMPRs, which avoids the disadvantages of the previous ones. Using the new concept, models to judge the consistency of HMPRs are built. Then, a consistency probability-based method to derive the hesitant fuzzy priority weight vector from HMPRs is offered. Considering the incomplete case, consistency-based programming models to determine the missing values are constructed. To address group decision making with HMPRs, a distance measure is defined to determine the weights of the DMs, and a consensus index is proposed. Then, a consistency and consensus-based group decision-making algorithm is performed. Finally, two practical examples, an investment problem and a water conservancy problem are offered to illustrate the feasibility and efficiency of the new algorithm. Comparison analysis from the numerical and theoretical aspects verifies the potential application of the new procedure.     

Large-scale group decision making with multiple stakeholders based on probabilistic linguistic preference relation

A large number of stakeholders take part in the process of decision making, namely, large-scale group decision making (LGDM) problems. Every stakeholder utilises a linguistic preference relation (LPR) to represent her/his preference information for alternatives. Then, a probabilistic LPR (PLPR) is established to represent the group preference. However, some stakeholders may only provide partial preference information about the alternatives. Thus, a PLPR with incomplete probabilities can be used to manage LGDM problems in complex environments. Based on the defined expected multiplicative consistency of PLPR, a probability computation model is established by mathematical programming to derive the missing probabilities of PLPR. In addition, an iterative algorithm to improve the consistency is proposed to obtain the PLPR with satisfactory consistency. Finally, a real-world investment decision-making problem with multiple stakeholders is solved to demonstrate the effectiveness of the proposed method.     

Qualitative hesitant fuzzy group decision making: An additively consistent probability and consensus-based perspective

Hesitant fuzzy linguistic preference relations (HFLPRs) can efficiently denote the hesitant qualitative judgments of decision makers. Consistency and consensus are two critical topics in group decision making (GDM) with preference relations. This paper uses the additively consistent concept for linguistic fuzzy preference relations (LFPRs) to give an additive consistency definition for HFLPRs. To judge the additive consistency of HFLPRs, 0-1 mixed programming models (0-1-MPMs) are constructed. Meanwhile, additive-consistency-based 0-1-MPMs to ascertain missing values in incomplete HFLPRs are established. Following the consistent probability of LFPRs, an algorithm to calculate the linguistic priority weighting vector is presented. In consideration of the consensus of GDM, a consistency-probability-distance-measure-based consensus index is defined, and an interactive improving consensus method is provided. Finally, a method for GDM with HFLPRs is offered that can address incomplete and inconsistent cases. Meanwhile, numerical examples are offered, and comparative analysis is made.     

面向企业集成的群体决策支持系统设计与实现

针对企业集成方案决策的需求，基于AHP和模糊决策方法，设计开发了一个基于Web的群体决策支持系统(EI—GDSS)，该系统的主要特点是：决策模型的构建可通过调用参考评价指标体系库中已定义的建造块进行定制，设计了一种模糊评价算法来计算权值向量，将决策过程分为中层评价和高层决策两个阶段，综合考虑了主、客观指标的不同处理方法和个体／群体一致性判别。     

A group decision-making model based on incomplete comparative expressions with hesitant linguistic terms

As a result of uncertainty and complexity for environments of decision-making, it is more suitable for decision makers to use hesitant fuzzy linguistic information. In this paper, a novel group decision making (GDM) model based on fuzzy linear programming is proposed for incomplete comparative expressions with hesitant fuzzy linguistic term set (HFLTSs). We establish an equivalence theorem of additive consistency between 2-tuple fuzzy linguistic preference relation (FLPR) and corresponding fuzzy preference relation. Based on this framework, a fuzzy linear programming is established to address incomplete comparative expressions with HFLTSs. It is more important that the proposed fuzzy linear programming has a double action, finding the highest consistent incomplete 2-tuple FLPR and increasing inconsistent 2-tuple FLPR to the additive consistent 2-tuple FLPR based on given incomplete comparative expressions with HFLTSs. By this means, a novel GDM model is constructed based on importance induced ordered weighted averaging operator. Finally, an investment decision-making in real-world is solved by the proposed model, which shows the result of GDM is effectiveness.     

基于犹豫语言判断矩阵的数据产品选择研究

犹豫语言判断矩阵作为一种新的判断矩阵,能够有效地处理决策信息为语言变量且决策者态度犹豫不行的决策问题。针对犹豫模糊语言信息环境下的数据产品选择问题,构建了一种基于犹豫语言判断矩阵的数据产品选择方法。该方法引入了犹豫语言判断矩阵的一些相关概念,包括加性一致性、一致性指数、可接受一致性;研究了犹豫语言判断矩阵一致性判定方法和特征矩阵的构造方法,并设计了一种收敛性算法用以改进犹豫语言判断矩阵的一致性;建立了基于犹豫语言判断矩阵的决策模型,并通过数据产品的选择实例说明提出的决策方法是合理和有效的。     

概率对偶犹豫模糊PROMETHEE多属性群决策算法

为解决犹豫模糊环境中由随机性和不确定性对实际决策造成偏差的多属性群决策问题,提出一种基于概率对偶犹豫模糊PROMETHEE的多属性群决策算法。构建各决策专家的概率对偶犹豫模糊信息矩阵;运用最大离差法与熵值法确定各决策专家与各指标属性的客观权重,结合改进的得分函数与偏离函数得到专家的综合决策评价信息矩阵;进而通过概率对偶犹豫模糊集与PROMETHEE结合的决策算法得到最终决策结果。将该算法运用于航空灾难事故应急响应方案评估的算例分析中,通过与TOPSIS、VIKOR及PDHFS决策算法的计算结果进行对比,验证了概率对偶犹豫模糊PROMETHEE多属性群决策算法的有效性与可靠性。