基于HFLAOWA算子的云计算系统优选

考虑犹豫模糊语言信息描述专家评价数据的全面性和便捷性,构建了基于犹豫模糊语言Archimedean有序加权平均(hesitant fuzzy linguistic Archimedean ordered weighted averaging,HFLAOWA)算子的多属性群决策模型.首先,基于严格Archimedeant...     

犹豫模糊语言PROMETHEE方法在川酒品牌评价中的应用

基于犹豫模糊语言集理论,提出一种犹豫模糊语言信息环境下的PROMETHEE多属性决策方法,并应用于川酒品牌评价决策问题中.研究表明,犹豫模糊语言集能够很好地描述和处理复杂定性信息环境下的川酒品牌评价与决策问题;所提出的犹豫模糊语言PROMETHEE算法简便, 且改进的偏好函数允许决策者根据其对方案的严格优于偏好对参数进行选择,可保证决策过程的科学性和决策结果的准确性.     

犹豫模糊语言群决策的共识性模型

针对犹豫模糊语言群决策问题,研究其共识性调整方法.首先,定义犹豫模糊语言术语集的距离测度;然后,基于该距离测度定义犹豫模糊决策矩阵间的共识性水平及其相关概念,建立共识性调整模型,该模型采用反馈机制,并且尽可能提供给专家较多的信息,以方便专家进行信息修正,达到群体共识;最后,通过具体实例说明了所提出的共识性方法的可行性和实用性.     

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。     

考虑个体累积共识贡献的犹豫模糊语言自适应共识模型

针对犹豫模糊语言信息下的多属性群决策问题,提出一种基于个体累积共识贡献的自适应共识决策模型.首先,利用犹豫模糊语言得分函数,基于经典的信息熵和相对熵理论,综合考虑同一属性下不同方案间的信息差异,以及各方案分别与正理想方案和负理想方案的信息差异,构建确定属性权重的优化模型;然后,提出个体累积共识贡献测度和全局共识测度,利用全局共识度进行共识控制,依据个体累积共识贡献度对专家权重进行自适应修正,构建一种新的犹豫模糊语言自适应共识过程.该过程的特点是对拥有较少合作的非全共识专家执行专家权重惩罚,而且专家权重的更新引起属性权重的自适应更新,反过来又影响个体共识贡献的累积.最后通过一个应急医疗设施选址的共识决策例子表明方法的可行性和有效性.     

基于累积前景理论的可变下标犹豫模糊语言多准则投资组合优化

将累积前景理论的价值函数引入投资组合决策,从行为金融学的角度对传统整数犹豫模糊语言术语集下标进行改进,改进后的可变下标犹豫模糊语言术语集不仅可以反映投资人对金融产品的不确定程度,还能描述投资人给出评价本身时对收益或损失的心理感知.在单投资者多准则评价视角下,利用可变下标的犹豫模糊语言多准则投资组合评价系统对不同股票进行量化评价,针对激进型、稳健型和保守型3类投资者分别提出收益最大化、风险最小化犹豫模糊语言投资组合模型,通过对等价非线性模型求解得到投资组合的最优解.最后,利用数值仿真验证所提出模型和方法的有效性.     

基于犹豫模糊语言多属性群决策的VIKOR扩展方法

针对犹豫模糊语言多属性群决策问题,提出了一种基于可能度分布的VIKOR方法。该方法首先将基于犹豫模糊语言的评价信息转化成可能度分布值,定义了新的距离公式,避免了传统犹豫模糊语言评价信息在计算过程中造成的信息扭曲。然后,设计了基于最大群体效用与最小个体遗憾两个目标的群体信息集结优化模型,并给出多属性群决策的VIKOR扩展方法。运用一个交通建设方案选择的案例分析验证了方法的有效性和优越性。     

基于优序关系的犹豫模糊语言多准则决策方法

犹豫模糊语言集是语言集和犹豫模糊集的扩展,受传统Electre方法的启发,构建基于优序关系的犹豫模糊语言多准则决策方法. 首先,给出犹豫模糊语言数的Hausdorff距离公式;然后,基于每一准则下方案评价的对比,建立犹豫模糊语言数的优序关系,并在此基础上,提出一种基于优序关系的犹豫模糊语言多准则决策方法;最后,通过算例表明了所提出方法的有效性和可行性.     

基于犹豫模糊语言的多阶段多属性决策方法

针对不确定语言条件下的决策问题,考虑专家偏好的阶段性差异,提出基于犹豫模糊语言的多阶段多属性决策方法。首先为了更准确地表达专家在决策过程中的犹豫性,采用犹豫模糊语言来表达专家的评估信息;其次考虑阶段权重的波动性,运用基于专家阶段性偏好的信息熵方法构建阶段权重优化模型确定阶段权重;然后利用最大化偏差法来求解属性权重,并采用基于平均解距离评价(EDAS)方法对备选方案进行排序;最后以某企业选取物流商问题为例,验证该方法的有效性和可行性。     

改进的犹豫模糊语言熵的一般公式与生成算法

由于现有的扩展犹豫模糊语言术语集的熵无法区分与补集相等的扩展犹豫模糊语言术语集的不确定性，并且对犹豫模糊语言信息中的犹豫性考虑得相对较少，无法全面地反映犹豫模糊语言信息的不确定性。改进了扩展犹豫模糊语言术语集的熵的定义，从模糊性和犹豫性两方面刻画了扩展犹豫模糊语言术语集的不确定性，分别定义了扩展犹豫模糊语言术语集的模糊熵和犹豫熵，给出了模糊熵和犹豫熵的一般公式与生成算法。定义了一个扩展犹豫模糊语言术语集的总熵，给出了总熵的一般公式。最后给出了一个基于犹豫模糊语言熵的高校教授晋升优选评估的多属性决策算例，通过比较分析说明了决策方法的可行性与有效性。     

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.     

Trust-based consensus reaching process for product design decision-making with heterogeneous information

Pursuing a consensual result is vital for selecting optimum product design schemes as it helps eliminate preference conflicts in product design decision-making (PDDM). As a dynamic and iterative activity, the consensus reaching process (CRP) of PDDM always involves heterogeneous, vague, and inconsistent information, which makes it challenging to adjust decision-makers’ judgement to achieve an acceptable consensus level. To address this issue, triangular fuzzy numbers were introduced to depict decision-makers’ heterogeneous judgement. The indicator weights were determined by integrating the fixed weight obtained from the interval analytic hierarchy process (IAHP) and the variable weight acquired using the maximizing deviation method. Decision-makers’ weights were identified through a combination of the uncertainty degree measured by fuzzy entropy and the consistency degree solved by a distance minimizing model of the PDDM matrix. A dynamic CRP for PDDM was proposed by adjusting decision-makers’ judgement based on their trust relationships and updating the PDDM matrix in an evolutionary manner. A case study is conducted to verify the feasibility and effectiveness of the proposed method.     

产品形态多意象蛛网灰靶决策模型

针对概念设计中多意象设计方案决策困难的现象,提出了一种产品形态多意象蛛网灰靶决策方法。首先,运用感性工学相关方法获取设计主体的认知数据,结合熵权法及博弈论思想构建基于设计主体认知数据的综合评价模型,并根据各意象的设计主体综合评价数据确定各意象的权重关系;其次,通过人工选择的方式从产品形态进化系统中选择多个进化方案,运用蛛网图表征各进化方案的意象关系,构建多意象蛛网灰靶决策模型,计算决策系数,对其进行比较排序,得到符合设计主体认知的相对最优方案;最后,应用灰色关联分析法验证该决策模型的可行性。结果表明,该模型能够帮助设计师在设计决策阶段快速、准确地确定符合多设计主体认知的多意象方案,为产品方案的多意象决策提供了新的理论和方法。     

Relationship between eye fixation patterns and Kansei evaluation of 3D chair forms

Understanding how to induce Kansei (emotion or affect) in consumers through form is critical in product design and development. Conventional Kansei evaluations, which involve subjectively evaluating the overall form of a product, do not clarify the effects of the individual parts of a product on people’s Kansei evaluation. A microscale analysis of eye movement of people looking at product form may redeem this flaw in subjective evaluation. However, simultaneously recording eye movement when people making Kansei evaluation is challenging, previous studies have typically investigated either the relationship between form and eye movement or the relationship between form and Kansei separately. The eye movement of people while performing Kansei evaluations on product forms still has not been clarified. To address this issue, the present study used an eye tracking system to analyze the changes in the fixation points of people performing various Kansei evaluations. Twenty participants were recruited for 8 Kansei evaluations on the form of 16 chairs by using the semantic differential (SD) rating, while their eye movements on these evaluations were tracked simultaneously. Through factor analysis on the data of Kansei evaluations, two principal factors, valence (pleasure) and arousal, were extracted from the 8 Kansei scales to constitute a Kansei plane which is compatible to Russell’s circumplex model (plane) of affect By adopting the factor scores of the 16 chairs as coordinates, the 16 chairs were mapped into the Kansei plane. Further analysis on the eye fixation on the chairs located in this plane concluded the following results: (a) Pleasure had a more significant effect on the participants’ visual attention compared to arousal; the participants required more fixation points when evaluating the chair form that induced displeasure. (b) The participants typically fixated on two parts of the chairs during their Kansei evaluations, namely the seat and the backrest, indicating that seats and backrests are the two primary features people consider when evaluating chairs. The results clarify the effect of various Kansei on eye movements; thereby enable predicting people’s Kansei evaluations of product forms through analyzing their eye movement.     

Signed distance‐based ORESTE for multicriteria group decision‐making with multigranular unbalanced hesitant fuzzy linguistic information

The objective of this study is to develop an integrated approach for solving multicriteria group decision‐making problems with multigranular unbalanced hesitant fuzzy linguistic term sets (HFLTSs). Firstly, a signed distance‐based transformation function is proposed to unify multigranular unbalanced hesitant fuzzy linguistic (HFL) assessments. Secondly, a mathematical programming model based on the maximum consensus is constructed to allocate decision‐makers (DMs)' weights objectively. Thirdly, a new signed distance‐based preference score function is defined to aggregate HFL assessments and determine the weak ranking of alternatives, and a novel preference, indifference, and incomparability test framework is constructed to identify the subtle relations among alternatives. On these bases, a signed distance‐based ORESTE (Organísation, rangement et Synthèse de données relarionnelles, in French) method, in which knowledge regarding criterion values and weights are expressed as multigranular unbalanced HFLTSs, is developed to obtain the ranking of alternatives. Finally, an illustrative example, followed by sensitivity and comparative analyses, is presented to verify the feasibility and effectiveness of the proposed approach.     

A dynamically weight adjustment in the consensus reaching process for group decision-making with hesitant fuzzy preference relations

The consensus reaching process is a dynamic and iterative process for improving group's consensus level before making a final decision in group decision-making (GDM). As the experts will express their opinions under their own intellectual level from different aspects, it is natural that the experts’ weights should reflect their judgment information. This paper proposes a dynamic way to adjust weights of decision-makers (DMs) automatically when they are asked to give original judgment information for GDM problems, in which the DMs express their judgment information by hesitant fuzzy preference relations (HFPRs). Two indices, an individual consensus index of hesitant fuzzy preference relation (ICIHFPR) and a group consensus index of hesitant fuzzy preference relation (GCIHFPR), are introduced. Normalisation of HFPRs with different numbers of possible values is taken into consideration for better computation and comparison. An iterative consensus reaching algorithm is presented with DMs’ weighting vector changing in each consensus reaching process and the process terminates until both the ICIHFPR and GCIHFPR are controlled within predefined thresholds. Finally, an example is illustrated and comparative analyses demonstrate the effectiveness of the proposed methods.     

产品外形设计中客户感性认知模型及应用

为了更好地利用客户的感性认知支持产品外形设计活动,提出一种产品外形设计中客户感性认知与产品外形特征关联模型.在分析产品外形设计中所涉及的客户感性认知特点的基础上,建立产品外形特征要素与客户感性认知要素的关联模式;以认知行为为标准,利用特征匹配实现了客户感性认知的识别与相似性分析;提出了基于模糊认知图的客户感性认知与产品外形特征关联模型,利用蚁群聚类算法确定模糊认知图的结构及邻接矩阵,从而获取客户感性认知以指导产品的外形设计.最后通过实例验证了该模型的有效性和实用性.     

The influence of user cognition on consumption decision-making from the perspective of bounded rationality

Consumer decision-making is related to the success or failure of enterprises, and products that cater to the cognitive preferences of users have become a focus of current research. Based on the theory of bounded rationality, this paper explores the cognitive process of consumer decision-making. Then, how product shape affects consumption decision-making is analyzed with eye-tracking technology. Finally, the design principle of the product form is further explored. The results demonstrate the following: (1) the perceptual cognition of users has a driving effect on consumption behavior; (2) as a key factor affecting the perceptual cognition of users, product form affects consumer decision-making by influencing the degree of approach motivation; (3) by establishing the mapping relationship between product form elements and user images, the principles of product form design can be more consistent with user image preferences. This study provides useful suggestions for how to increase the purchase behavior of users from the perspective of bounded rationality.     

融合贝叶斯网络与前景理论的产品工业设计多阶段决策方法#br#

针对产品工业设计决策中的不确定性与单一设计决策阶段难以准确描述全局决策结果的问题,引入三参数区间灰数对决策者的意见进行描述,构建贝叶斯网络(BN)模型学习用户群体对市场上现有成熟产品的决策信息,获得目标产品工业设计方案在各决策属性上的状态分布概率。为反映决策者对设计方案感知相对收益和损失的心理行为,融合前景理论(PT)与 BN 构建不同决策阶段产品工业设计方案的前景价值函数,以认知递进假设建立优化模型计算产品工业设计决策多阶段权重,通过综合前景价值计算判断设计方案优劣。以数控磨床工业设计方案决策的多阶段融合为例验证了方法的有效性,结果表明该方法能够引入用户群体的多阶段意见偏好估计设计决策属性的概率分布,以前景价值实现产品工业设计多阶段决策信息的有效集结,提高设计决策的全局性和科学性。