模糊偏好关系下考虑从众行为的群体共识决策方法

随着决策面临的环境越来越复杂,个人决策因其局限性难以达到有效决策的标准,致使群体决策变得更为常见;而当决策者行动时,常需考虑他人的判断和行为,使得从众行为成为群体决策中的重要影响因素.因此,文章基于模糊偏好关系提出一种考虑从众行为的群体共识决策方法,能有效节省达成共识所付出的成本.首先,根据模糊偏好关系的特征,设计一致性检验方法和调整模型,为后续的共识达成提供可靠的偏好关系.其次,考虑到专家受到群体规范的压力而产生从众行为,从而对初始效用值进行修正.然后,提出考虑从众行为的最小成本共识模型,进一步设计相应的共识达成算法.最后,计算各已选方案到理想点的距离,运用TOPSIS方法对已选方案进行排序,并通过一个企业产品升级改良的算例来分析说明所提方法是有效的和可行的.     

基于共识性测度的概率语言多准则群决策方法研究

针对准则值为概率语言术语集的决策问题,提出一种基于共识性测度的概率语言多准则群决策方法.首先,方法定义概率语言共识性测度公式,据此判断个体决策信息是否满足共识性检验.其次,建立考虑决策者协作意愿的群体共识反馈调整模型及权重惩罚体系.此外,利用网络层次分析法(ANP)和共识性测度公式构建指标定权模型,模型可有效解决指标间互相影响导致的权重计算失准问题.随后,提出改进的TODIM决策方法,结合准则权系数及通过共识性检验的群决策矩阵,对方案进行择优排序.最后,通过算例分析验证了该方法的有效性.     

基于区间数偏好信息的专家群体共识性研究

针对群决策中基于区间数偏好信息的共识性问题,给出了一种新的分析方法.首先给出了有关区间数和区间数决策矩阵的定义及若干性质;然后.通过定义有关专家群体判断关于方案针对指标的落影函数和专家群体关于方案针对指标的重心值,给出了群决策中基于区间数决策矩阵的共识性的分析方法和非共识的调整方法.最后,通过一个算例说明给出的分析方法.     

基于白化值的区间DEA建模

传统数据包络分析要求输入输出数据为精确数,然而在某些实际应用中,区间形式的数据相较于精确数更容易获得.将区间数转化为白化值,并基于传统C~2R模型提出了基于白化值的区间C~2R模型.考虑到决策单元的有效性不易通过基于白化值的区间C~2R模型来判断,因此将非阿基米德无穷小概念引入到上述模型,构建了具有非阿基米德无穷小的区间C~2R模型.此外,还给出了用于判断决策单元有效性的区间目标规划方法:分别通过G_(IC~2R)模型和WG_(IC~2R)模型判断决策单元是否为区间DEA有效与区间弱DEA有效.     

基于改进的GRA-PDEA模型的应急系统优化选址

从应急系统优化选址的实践需求出发,构建了多输入/多输出、多种数据类型的决策指标体系,给出了针对成本/效益指标的区间型、模糊型属性值的规范化处理模型,得到各备选方案的指标属性值规范化矩阵.采用了带决策者偏好的数据包络分析模型进行优化选址决策,体现了在应急系统优化选址问题中应注重的相对有效性决策策略,同时引入基于灰色关联分析的定权模型,使决策过程既发挥决策者的主观能动性,又规避其主观臆断.通过给出备选方案的实证分析,较好地实现了应急系统优化选址的目的,选址结果与实际情况也是相吻合的.     

基于时隙区间滑动的全过程时间限制车流组织协调优化

对全过程时间限制车流协调优化问题进行描述。基于该问题随机动态特性,将计划周期划分为若干决策时隙区间,并以决策时隙区间为单位进行建模求解。定义运输任务即时成本和未来成本,并构建决策时隙区间内最优分配网络。通过决策时隙区间逆向滑动过程设计,逐步估计各决策时隙区间内相应运输任务的未来成本,并将其引入模型构建车流组织协调优化问题异构模型。最后设计试验演进问题求解过程,验证方法的有效性。     

考虑决策者风险偏好的区间直觉模糊多属性群决策方法

提出了一种考虑决策者风险偏好且属性权重信息不完全的区间直觉模糊数多属性群决策方法。同时考虑相似度和接近度,确定每一属性的决策者权重。为了考虑决策者风险偏好对决策结果的影响和避免区间直觉模糊矩阵的渐进性,引入了决策者风险偏好系数,将集结后的综合决策矩阵转换成区间数矩阵。然后,为了客观地求出属性权重信息不完全环境下属性的权重,构建了基于区间直觉模糊交叉熵的属性权重目标规划模型,该模型不仅考虑了评价值的偏差,也强调了评价值自身的可信度。最后,通过研发项目选择问题的实例分析说明了所提方法的合理性和优越性。     

基于决策者偏好的区间型属性熵权确定方法

给出了一种基于决策者主观偏好的区间型属性熵权决策方法。将决策者的乐观测度引入到区间型多属性决策问题中,结合区间型多属性决策中确定熵权的方法,建立了既能反映决策者乐观测度,又能充分利用已有客观信息的区间型熵权优化模型。最后将其用于航天研制项目风险决策,实例表明了该方法的实效性。     

基于物理规划的工程项目综合均衡优化

质量、工期和成本是工程项目三大主要控制目标,对于工程项目中质量-工期-成本综合均衡优化问题,传统的基于权重的决策方法存在各目标权重难以合理确定的问题.为此引入物理规划方法建立工程项目质量-工期-成本综合均衡优化模型.决策者只需设定各目标的偏好,即可通过该均衡优化模型获得符合决策者偏好的优化方案,使决策过程更加符合工程实际,避免了确定无实际物理意义的各目标权重的问题.通过桥梁工程实例验证了该方法的有效性和实用性.     

区间粗糙数序信息系统下的优势关系粗糙集模型

以区间粗糙数为研究对象,提出了基于区间优势度的区间粗糙数比较公式,通过引入参数α调节决策者对区间粗糙数下近似和上近似的重视程度,以充分考虑决策者的风险偏好。在此基础上,引入优势度阈值β并定义了基于优势度的优势关系粗糙集模型,进一步给出了此模型框架下的四种排序方法。对优势度、优势关系及排序方法的相关性质进行了证明,最后通过算例验证模型与排序方法的合理性。     

解决一类群决策问题的改进德尔菲法

专家综合评价属于委员会形式的群决策问题,提出了基于一致性分析的群决策机制和基于OWA算子的群决策机制,用来弥补常用机制的缺陷;介绍了判断群体意见分歧特征和定量判断标准;提出了基于一致性分析的改进德尔菲法,介绍了这种方法的思想、特点和应用步骤;分析了这类群决策的人员组成和工作程序图.     

An evidential reasoning based consensus model for multiple attribute group decision analysis problems with interval-valued group consensus requirements

With the aim of modeling multiple attribute group decision analysis problems with group consensus (GC) requirements, a GC based evidential reasoning approach and further an attribute weight based feedback model are sequentially developed based on an evidential reasoning (ER) approach. In real situations, however, giving precise (crisp) assessments for alternatives is often too restrictive and difficult for experts, due to incompleteness or lack of information. Experts may also find it difficult to give appropriate assessments on specific attributes, due to limitation or lack of knowledge, experience and provided data about the problem domain. In this paper, an ER based consensus model (ERCM) is proposed to deal with these situations, in which experts’ assessments are interval-valued rather than precise. Correspondingly, predefined interval-valued GC (IGC) requirements need to be reached after group analysis and discussion within specified times. Also, the process of reaching IGC is accelerated by a feedback mechanism including identification rules at three levels, consisting of the attribute, alternative and global levels, and a suggestion rule. Particularly, recommendations on assessments in the suggestion rule are constructed based on recommendations on their lower and upper bounds detected by the identification rule at a specific level. A preferentially developed industry selection problem is solved by the ERCM to demonstrate its detailed implementation process, validity, and applicability.     

基于累积共识贡献的不确定语言共识决策方法

针对不确定加型语言偏好信息下的群决策问题,提出一种基于累积共识贡献的自适应式语言共识决策方法。首先,将不确定加型语言偏好转化为不确定二元语义偏好,定义个体一致度与个体共识偏度,并利用它们构建确定专家初始权重的优化模型;然后,利用不确定二元语义的可能度构造集结模糊评价矩阵以及方案的集结群体偏好,提出专家累积共识贡献测度和群体共识测度,通过对拥有较少合作的专家权重进行惩罚让群体自适应地达成共识,无需强迫专家修改其观点,提出一种群体共识决策方法对方案排序择优。最后,通过一个算例说明方法的可行性和有效性。     

An approach to group decision making based on interval multiplicative and fuzzy preference relations by using projection

This paper presents a consensus model for group decision making with interval multiplicative and fuzzy preference relations based on two consensus criteria: (1) a consensus measure which indicates the agreement between experts’ preference relations and (2) a measure of proximity to find out how far the individual opinions are from the group opinion. These measures are calculated by using the relative projections of individual preference relations on the collective one, which are obtained by extending the relative projection of vectors. First, the weights of experts are determined by the relative projections of individual preference relations on the initial collective one. Then using the weights of experts, all individual preference relations are aggregated into a collective one. The consensus and proximity measures are calculated by using the relative projections of experts’ preference relations respectively. The consensus measure is used to guide the consensus process until the collective solution is achieved. The proximity measure is used to guide the discussion phase of consensus reaching process. In such a way, an iterative algorithm is designed to guide the experts in the consensus reaching process. Finally the expected value preference relations are defined to transform the interval collective preference relation to a crisp one and the weights of alternatives are obtained from the expected value preference relations. Two numerical examples are given to illustrate the models and approaches.     

Deffuant model with general opinion distributions: First impression and critical confidence bound

In the Deffuant model for social influence, pairs of adjacent agents interact at a constant rate and mix up their opinions (represented by continuous variables) only if the distance between opinions is short according to a threshold. We derive a critical threshold for the Deffuant model on , above which the opinions converge toward the average value of the initial opinion distribution with probability one, provided the initial distribution has a finite second order moment. We demonstrate our theoretical results by performing extensive numerical simulations on some continuous probability distributions including uniform, Beta, power‐law and normal distributions. Noticed is a clear differentiation of convergence rate that unimodal opinions (regardless of being biased or not) achieve consensus much faster than even or polarized opinions. Hereby, the emergence of a single mainstream view is a prominent feature giving rise to fast consensus in public opinion formation and social contagious behavior. Finally, we discuss the Deffuant model on an infinite Cayley tree, through which general network architectures might be factored in. © 2013 Wiley Periodicals, Inc. Complexity 19: 38–49, 2013     

Multiple criteria group decision-making with generalized interval-valued fuzzy numbers based on signed distances and incomplete weights

Decision-making information provided by decision makers is often imprecise or uncertain, due to lack of data, time pressure, or the decision makers’ limited attention and information-processing capabilities. Interval-valued fuzzy sets are associated with greater imprecision and more ambiguity than are ordinary fuzzy sets. For these reasons, this paper presents a signed distance-based method for handling fuzzy multiple-criteria group decision-making problems in which individual assessments are provided as generalized interval-valued trapezoidal fuzzy numbers, and the information about criterion weights are not precisely but partially known. First, concerning the relative importance of decision makers and the group consensus of fuzzy opinions, all individual decision opinions were aggregated into group opinions using a hybrid average with weighted averaging and signed distance-based ordered weighted averaging operations. Next, considering a decision situation with incomplete weight information of criteria, an integrated programming model was developed to estimate criterion weights and to order the priorities of various alternatives based on signed distances. In addition, several deviation variables were introduced to mitigate the effect of inconsistent evaluations on the importance of criteria. Finally, the feasibility of the proposed method is illustrated by a numerical example of a multi-criteria supplier selection problem. Furthermore, a comparative analysis with other methods was conducted to validate the effectiveness and applicability of the proposed methodology.     

Unanimous opinions in social influence networks

In this paper, I show that persons reach unanimous opinions even when they have different initial opinions and different social influences in social influence networks. Friedkin and Johnsen introduced a model of social influence networks, and identified conditions for initially diverse opinions to converge. However, they did not examine conditions of “unanimous” convergence. Hence, I provide sufficient conditions of such unanimous consensus by focusing on three typical but conflicting social influences: the equal influence, the influence of the lowest opinion, and no influence. I show that unanimous opinions occur even when persons have antagonistic social influences such as the equal influence and the influence of the lowest opinion. I also demonstrate that the most cooperative type is the equal influence, but the most central type is the no influence.     

基于区间二型梯形模糊集的应急物资储备动态协同决策模型

重大灾害下应急物资储备决策是阻止突发灾难蔓延的有效手段之一。针对救灾信息具备不确定性与复杂性特点,构建基于区间二型梯形模糊集的应急物资储备动态协同决策模型,并给出应急物资储备策略。利用区间二型模糊集理论的决策方案并结合比例分析法(COPRAS),构建常态环境下应急物资供应商选择的群决策模型,解决不相容群决策属性之间的冲突问题;进而,充分考虑“救灾阶段性动态时间因素”对储备决策的影响,构建动态救灾环境下应急物资储备结构模糊优化模型,实现常态决策与非常态应急决策之间的动态协同;最后,以2012年云南丽江“6.14”突发特大山洪灾害为实例进行数值分析,验证该动态协同决策模型的合理性与可行性,能有效解决动态救灾环境下应急物资储备结构优化问题。     

Chaotic social interaction via endogenous reactivity

We propose a framework to analyse the dynamical process of decision and opinion formation of two economic homogeneous and boundedly rational agents that interact and learn from each other over time. The decisional process described in our model is an adaptive adjustment mechanism in which two agents take into account the difference between their own opinion and the opinion of the other agent. The smaller that difference, the larger the weight given to the comparison of the opinions. We assume that if the distance between the two opinions is larger than a given threshold, then there is no interaction and the agents do not change their opinion anymore. Introducing an auxiliary variable describing the distance between the opinions, we obtain a one-dimensional map for which we investigate, mainly via analytical tools, the stability of the steady states, their bifurcations, as well as the existence of chaotic dynamics and multistability phenomena.     

多属性群决策算法及一致性分析研究

在多属性群决策中 ,集结群体意见之前必须先对群体的决策数据进行一致性分析 ,以确保群体作出的决策符合客观实际 .提出了群决策的三种三维层次模型 ;用欧几里得距离 ( Euclidean Distance)表示个人决策中方案的评价值 ;然后设置一致性指标值α,作为群体数据一致性的判断依据 ;提出了满足一致性基础上的一种群决策方法 ;最后用实例说明了算法的使用步骤 .