物流服务质量评价指标排序研究

提出物流服务质量评价指标排序对物流企业满足客户需求、提升核心竞争力的重要意义.提出三角模糊集、正态模糊集用于权重设置的具体途径,应用OWA算子于客户评价数值加权,并拓展基本原理和方法,使其对极端评分值有所抑制.以鸿迅物流为实证研究对象,应用直觉模糊集及其IFHA集成方法于物流服务质量评价指标排序,并得出u7＞u6 ＞u5 ＞u2 ＞u10 ＞u9 ＞u1＞u8＞u4＞u3的结论.     

基于直觉模糊优化的双边匹配决策

为了实现不确定信息环境下的双边满意匹配，提出基于直觉模糊优化的匹配决策方法。利用直觉模糊集理论中隶属度和非隶属度的概念，将经典匹配决策模型中双目标函数转换为反映匹配双方总体满意度的单目标函数，模型中同时纳入公平性因素。通过设计交互式算法，在满足一定的公平性条件下实现总体满意度最大化。该算法为匹配决策过程注入了灵活性和协调性，具有一定的实用性和参考价值。     

Vague集之间的相似度量及其在方案决策中的应用

针对模糊集的推广形式--Vague集,描述了Vague集中隶属度的三维含义、不确定隶属度对肯定与否定隶属程度的影响以及欧氏距离的表示,提出Vague集的相似度量与工程方案决策方法。在工程设计方案决策中,Vague集之间的相似度量是评价设计方案接近期望方案（理想方案）的度量,相似度量值越大,设计方案接近期望方案越好。最后通过实例阐明Vague集之间的相似度量在工程设计方案决策中的可行性和合理性。     

机械产品模块划分方案的评价与决策

把层次分析法(AHP)和有效价值法综合应用于模块划分方案的评价与决策。其过程主要包括:确定模块划分方案的评价准则、确定各评价目标所占的权重、各评价目标的价值量度、特性值与价值的对应关系、计算模块划分方案的总价值几个步骤,最后根据总价值进行决策。     

施工机械配套方案的模糊优选

针对施工机械设备配套方案设计和研究的复杂性与模糊性,提出采用模糊优选方法与层次分析法相结合对多个方案进行综合评价和优选。论述了评价系统的建立、评价指标隶属度的确定以及用层次分析法确定各评价指标之间的相对权重。通过一算例说明了方案优选的过程。模糊优选这一方法简单实用,可为施工机械设备配套方案的设计和研究提供科学决策的依据和手段,具有广泛的实用价值。     

Vague集Vague图及其在ITS物流中的应用

在模糊集（fuzzy set）的基础上讨论了“双模糊集”Vague集的基本概念和运算形式，具体讨论了Vague聚类分析、Vague多准则决策、Vague图等问题及其在现代物流中的应用。最后给出根据正、负两方面效益选择运输方案的Vague集在物流中的应用实例。     

社会网络环境下融合概率语言和QUALIFLEX的 绿色包装评价方法

为科学合理地评价绿色包装方案,提出一种社会网络环境下,融合概率语言和QUALIFLEX的绿色包装评价方法。先确定绿色包装评价指标体系并利用概率语言术语集（PLTS）表达决策专家的评价信息;然后分别利用决策专家间信任关系网络和决策专家-准则偏好关系矩阵,计算决策专家与准则的权重;最后结合QUALIFLEX方法确定备选绿色包装方案的优序关系。通过与其他方法进行对比,验证了所提出方法的有效性和合理性。     

基于模糊群决策的天津特色食品包装SPA–TOPSIS评价

目的 针对地方特色食品包装设计需兼具功能性和文化性的特征,开展包装设计方案评价,有效辅助设计开发过程,丰富地方特色食品包装设计的思路。方法 以天津特色食品——麻花包装为研究对象,构建分层次的包装评价准则框架;采用基于梯形模糊数的专家评价法来获得备选方案在各准则上的评分,通过群决策来集结多位专家的评判意见,进而求解得到备选方案的准则值;引入集对分析理论(SPA),采用连接向量距离来替换经典TOPSIS中的欧氏距离,提出SPA–TOPSIS评价方法来实现备选方案的评价和排序。结果 针对麻花的6种包装设计方案,实施了基于模糊群决策的SPA–TOPSIS评价,6种包装设计方案与正理想解的贴近度依次为0.55、0.46、0.53、0.49、0.56、0.44,方案5为最优方案。结论 通过天津特色食品包装评价,完善了城市文化内涵包装设计的理念,为包装的文化性设计提供了重要支持。     

融合社会网络和优序关系的绿色包装评价方法

在绿色包装方案选择时,针对准则数量显然超过方案数量且在社会网络环境下群体决策中,决策专家间信任关系及对准则的偏好关系复杂的特点,提出融合社会网络和优序关系的绿色包装评价方法。先确定绿色包装方案评价指标,并利用概率语言术语集表达决策专家的评价信息;然后利用社会关系网络计算决策专家权重,并利用偏好关系网络结合可能度公式计算准则权重;最后用QUALIFLEX方法确定备选绿色包装方案的优序关系。通过与其他方法进行对比,验证了所提方法的有效性和合理性。     

基于犹豫模糊语言信息的权重信息部分可知TOPSIS方法

基于犹豫模糊集和语言变量,给出犹豫模糊语言变量的定义.采用犹豫模糊语言变量建模决策过程中的不确定信息,在考虑属性权重信息部分可知的情况下,提出了一个新的多属性决策方法.首先,利用犹豫模糊语言变量给出方案的评价值.然后,采用极大偏差法建立线性规划模型确定属性权重向量.最后,采用TOPSIS方法对方案进行排序,并且给出了具体的方案排序方法.为了说明新方法的可行性和有效性,我们将其应用到地铁壁画的评价上.实例表明新方法确实是一个简单有效的方法.     

The incorporation of the Taguchi and the VIKOR methods to optimize multi-response problems in intuitionistic fuzzy environments

The Taguchi method is a powerful method of solving quality problems in various fields of engineering. However, this method was developed to optimize single-response processes. In many multi-response optimization problems, the important response is determined subjectively, based on knowledge or experience. However, using only exact numbers to represent this importance is problematic, because there is uncertainty and vagueness. The concept of intuitionistic fuzzy sets (IFSs) is a powerful method for characterization, using a membership function and a non-membership function. This paper proposes an efficient VIKOR method that optimizes multi-response problems in intuitionistic fuzzy environments. The importance weights of various responses are evaluated in terms of IFSs. In the proposed method, the similarity measure between IFSs is used to determine the crisp weights of the responses. This scheme eliminates the need for complicated intuitionistic fuzzy arithmetic operations and increases efficiency in solving multi-response optimization problems in intuitionistic fuzzy environments. Two case studies: plasma-enhanced chemical vapor deposition and a double-sided surface mount technology electronic assembly operation are used to demonstrate the effectiveness of the proposed method.     

直觉模糊数的表示和结构刻划

本文给出了直觉模糊数的表示定理:包括区间表示、函数表示、嵌入定理,并将直觉模糊数空间嵌入到一类特殊的二维模糊数空间—方模糊数空间,给出了直觉模糊数的结构定理;最后,利用方模糊数与一般二维模糊数的逼近定理,给出了二维模糊数的直觉模糊数逼近。     

An optimal solution of energy scheduling problem based on chance-constraint programming model using Interval-valued neutrosophic constraints

Optimization and Engineering - Neutrosophic sets have been commenced as a generalization of crisp, fuzzy and intuitionistic fuzzy sets to depict vague, incompatible and deficient information about...     

Intuitionistic fuzzy approach for enhancement of low contrast mammogram images

Mammogram image enhancement is very much necessary in diagnosing breast cancer or tumor at an early stage. Nonuniform illumination and low contrast images are commonly encountered in mammogram images. Conventional enhancement algorithms produce either some artifacts or cannot highlight minute details present in the images, particularly when dealing with mammogram images. In this article, we propose a new mammogram image enhancement scheme using Atanassov's intuitionistic fuzzy set (IFS) theory. IFS considers two uncertainties—membership and nonmembership degree apart from membership degree as in fuzzy set theory. As mammogram images are low contrast images and many of the image definitions are vague/unclear, so IFS theory may be suitable for better image enhancement. Initially, the image is transformed to an intuitionistic fuzzy image using a novel intuitionistic fuzzy generator. Hesitation degree is computed and using the hesitation degree, two membership levels are computed to form an interval type 2 fuzzy set. These two membership functions are then combined using Zadeh's fuzzy t-conorm to form a new membership function. Threshold of interval type 2 fuzzy image is obtained using restricted equivalence function. Using the threshold, modified fuzzy hyperbolization is carried out. Real data experiments demonstrate that the proposed algorithm has better performance on contrast and visual quality of the images both quantitatively and qualitatively when compared with different existing methods.     

Failure mode and effect analysis using the hesitant intuitionistic fuzzy hybrid GRP approach with ordered comprehensive weights

Failure mode and effect analysis (FMEA), a multidisciplinary reliability analysis tool based on team evaluations, has been widely used in various industries. There are three critical issues in FMEA: the conversion of linguistic evaluations, the weights of risk factors, and the ranking mechanism of failure modes. Scholars have used various fuzzy theories and multi-attribute decision-making (MADM) methods to improve traditional FMEA, but there are still deficiencies. In this paper, the hesitant intuitionistic fuzzy set (HIFS), a concept that combines the intuitionistic fuzzy set (IFS) and the hesitant fuzzy set (HFS), is introduced into FMEA to convert linguistic evaluations. Some operators based on HIFS are proposed to process the converted data. Among them, a hesitant intuitionistic fuzzy comprehensive weighted Hamming distance (HIFCWHD) operator is proposed to compute the ordered comprehensive weight, effectively weakening the effect of extreme scores on results. The gray relational projection (GRP) method is adopted to determine the risk priority order of the failure modes. Finally, we give an illustrative case to demonstrate the effectiveness of the proposed FMEA method.     

Intuitionistic Fuzzy Petri Nets Model Based on Back Propagation Algorithm for Information Services

Intuitionistic fuzzy Petri net is an important class of Petri nets, which can be used to model the knowledge base system based on intuitionistic fuzzy production rules. In order to solve the problem of poor self-learning ability of intuitionistic fuzzy systems, a new Petri net modeling method is proposed by introducing BP (Error Back Propagation) algorithm in neural networks. By judging whether the transition is ignited by continuous function, the intuitionistic fuzziness of classical BP algorithm is extended to the parameter learning and training, which makes Petri network have stronger generalization ability and adaptive function, and the reasoning result is more accurate and credible, which is useful for information services. Finally, a typical example is given to verify the effectiveness and superiority of the parameter optimization method.     

基于直觉模糊张量的决策方法及其应用

对具有高维数据特征的直觉模糊决策问题进行了研究,定义了直觉模糊张量的一般形式和运算法则;建立了基于直觉模糊张量的广义直觉模糊加权平均算子,探索了广义直觉模糊加权平均算子的基本性质;证明了广义直觉模糊加权平均算子是直觉模糊加权平均算子的一般形式。提出了基于广义直觉模糊加权平均算子的决策方法,通过算例验证了该方法能够有效解决具有高维数据特征的直觉模糊决策问题。     

基于模糊设计准则的机械可靠性优化设计研究

按照应力-强度分布干涉和模糊理论,对机械模糊可靠性优化设计方法进行系统的研究,提出了剩余可靠度的概念,建立了数学模型,给出了设计实例。研究表明：仅仅以实现要求的可靠度为目标的一般模糊可靠性设计由于不能考虑其他条件对设计变量取值的约束作用,往往导致设计结果不具可行性而失去实际意义。可靠性优化设计将模糊可靠性条件与其他所有限制条件一起作为设计约束,在设计空间围成一个可行设计域,然后按照设计目标要求用一定方法寻求可行域内的最优设计点,从而保证了设计结果既具可靠性,又具可行性和最优性。     

Trapezoidal Intuitionistic Fuzzy Aggregation Operator Based on Choquet Integral and Its Application to Multi-Criteria Decision-Making Problems

The Choquet integral can serve as a useful tool to aggregate interacting criteria in an uncertain environment. In this paper, a trapezoidal intuitionistic fuzzy aggregation operator based on the Choquet integral is proposed for multi-criteria decision-making problems. The decision information takes the form of trapezoidal intuitionistic fuzzy numbers and both the importance and the interaction information among decision-making criteria are considered. On the basis of the introduction of trapezoidal intuitionistic fuzzy numbers, its operational laws and expected value are defined. A trapezoidal intuitionistic fuzzy aggregation operator based on the Choquet integral is then defined and some of its properties are investigated. A new multi-criteria decision-making method based on a trapezoidal intuitionistic fuzzy Choquet integral operator is proposed. Finally, an illustrative example is used to show the feasibility and availability of the proposed method.