n-直觉多边形模糊有序加权距离算子及其在绿色供应商评价中的应用

n-直觉多边形模糊集(n-intuitionistic polygonal fuzzy sets)是三角形直觉模糊集(TIFS)和梯形直觉模糊集(TRIFS)的扩展形式。针对决策信息为n-直觉多边形模糊集的多属性决策问题,提出了一种基于有序加权距离测度的多属性决策方法。在分析现有n-直觉多边形模糊集距离测度方法不足的基础上,首先概括了n-IPFSs的概念和运算法则;其次提出了n-直觉多边形模糊有序加权距离算子(n-IPFOWD),并给出了该测度的权重确定方法;最后提出了一种基于n-直觉多边形模糊有序加权距离算子(n-IPFOWD)的多属性决策方法,并用绿色供应商评价实例验证了该方法的可行性和有效性。     

基于区间毕达哥拉斯模糊相似测度的多属性群决策方法研究

毕达哥拉斯模糊集是对模糊集和直觉模糊集的推广,本文在实型广义加权平均算子的基础上提出一种新的测度——区间毕达哥拉斯模糊余弦相似测度,并提出了一种基于该相似测度的多属性决策方法。首先,介绍区间毕达哥拉斯模糊数的概念以及运算法则;其次提出了区间毕达哥拉斯模糊有序加权余弦相似测度,分析了其单调性、有界性等相关性质以及其多种推广形式,并将其运用至多属性群决策问题中。最后,将这种群决策方法运用在推选优秀学生的方案选择中,通过改变参数及权重向量取值的方法得到不同集结结果,体现了本文提出的方法的有效性及可行性。     

犹豫模糊软集及其在多属性群决策中的应用

研究了评价值信息为犹豫模糊软集形式的多属性群决策问题。首先介绍了犹豫模糊软集的概念,并讨论了其相关运算及性质。考虑群决策中可能存在各专家权重系数完全未知的情况,定义了犹豫模糊软矩阵及其得分矩阵,并建立基于得分矩阵间关联系数的最优规划模型,以此确定各专家的权重。然后,基于犹豫模糊软集信息,定义了两种集成算子,即犹豫模糊软集算术加权算子和犹豫模糊软集几何加权算子,并利用水平软集工具计算各方案的机会值,得出最优决策。最后,提出一种基于犹豫模糊软集环境下的多属性群决策方法。     

一种基于梯形模糊中心的不确定多属性决策Topsis方法

文章针对只有部分属性权重信息且属性值以梯形模糊数形式给出的模糊多属性决策问题,提出一种基于梯形模糊数的中心的多属性决策方法。该方法建立一个非线性规划模型,通过求解该模型得到属性的权重向量。然后根据传统的Topsis方法,计算各方案属性值加权后的模糊中心与正负理想中心的贴近度的大小进行排序择优,最后给出算例。     

直觉模糊熵的多属性在企业选拔管理人员中的应用

本文采用一种基于熵程序的直觉模糊多属性决策程序的方法,建立了一种选拔最优秀的管理人员的直觉模糊多属性决策模型。首先计算直觉模糊矩阵,然后确定各个属性的权重,最后利用标准得分矩阵和加权平均算子计算各个人员的综合评分,并以此作为决策依据。最后通过实例验证了算法的有效性。     

多属性决策方法及其在节能减排中的应用研究

通过对直觉模糊数的区间化处理,把直觉模糊多属性决策转化为属性值为区间数的多属性决策.基于决策者的主观偏好值和客观偏好值的总偏差最小化原则得到属性权重,从而给出了一种直觉模糊多属性决策方法.最后利用所提出的方法对企业的节能减排效果进行了评价研究.     

基于IFHA算子和IFHG算子的空间数据质量评价方法

直觉模糊集多属性决策对空间数据质量评价是模糊评价和多属性评价模糊评价的综合评价方法。IFHA算子和IFHG算子是既考虑了数据质量的肯定、否定以及不确定性多种因素,又夹杂着合适的位置权重的研究方法,其方法与传统的评价方法相比较能更加真实、细腻地描述和刻画客观世界的模糊性本质。文章通过算例进行比较分析,解释其原因与不足。     

概率有序加权算子P-OWG在公路方案优选中的应用

在公路方案优选的多属性方案决策中,运用概率有序加权几何(P-OWG)算子对各方案的属性值进行集成,根据得出的综合属性值对各方案进行排序和优选,可以十分方便的选出最优的方案。     

基于多属性评价的项目投资决策方法

本文根据工程项目投资决策过程的特点,提出基于有序加权平均算子(OWA)和有序加权几何平均算子(OWGA)的多属性群决策方法。案例分析表明,该方法在工程项目的投资决策应用中具有可行性。     

基于直觉模糊的医院患者满意度研究

医院患者满意度综合反映了医院医疗服务水平。文章基于直觉模糊集理论建立了一个多级直觉模糊满意度计算模型,利用直觉模糊集算子有效地诱导出直觉模糊满意度,将定性与定量的方法结合起来进行满意度计算,使计算结果信息量更大、更加科学合理且自动化程度高。以商洛职业技术学院附属医院为例,通过问卷调查数据,基于直觉模糊满意度模型,计算医院患者满意度。探索一些指标满意度较低的原因;并针对患者普遍不满意的指标提出具体建议。     

基于直觉模糊集的供应链战略合作伙伴选择

企业建立良好的战略合作伙伴关系可以使供应链产生更强的竞争优势。文章通过对供应链战略合作伙伴的基本原则和影响因素进行分析,建立了合作伙伴的评价指标,运用直觉模糊集广义混合加权集结算子,对合作伙伴选择问题进行了综合评价,并通过实例说明该方法能够很好的解决供应链战略合作伙伴选择的实际问题,具有科学性和可操作性。     

具有模糊加工时间的Flexible Job-Shop Scheduling问题的研究

采用梯形模糊数来表征柔性生产系统中的时间参数,并在此基础上对具有模糊加工时间的柔性作业车间最小化制造跨度调度问题进行了描述。然后给出了基于粒子群优化的柔性作业车间调度模型。最后通过实例验证了模型的有效性。     

基于 QFD的物流供应商的选择问题研究

为降低物流供应商选择过程中的模糊不确定性和主观性,将QFD、三角模糊数和Kano模型三者结合起来提出一种新的物流供应商的选择方法。文中应用QFD,首先结合三角模糊数法和专家评估法确定企业需求指标项的初始相对权重、企业需求与技术特性间的关系矩阵和各技术特性间的关联矩阵,同时对各三角模糊数进行去模糊处理。然后,根据权重对全部企业需求进行排序,将排序结果区分为Kano模型中的3类需求,并用Kano系数表示,同时据此计算各技术特性的权重值。最后,综合技术特性权重值和候选物流供应商在各特性上的分值,经加权求和得出各供应商的总得分。通过算例证实了所提方法的可行性和有效性,能够给企业提供具体的、可操作的指导。     

Simultaneous selection and weighting of moments in GMM using a trapezoidal kernel

This paper proposes a novel procedure to estimate linear models when the number of instruments is large. At the heart of such models is the need to balance the trade off between attaining asymptotic efficiency, which requires more instruments, and minimizing bias, which is adversely affected by the addition of instruments. Two questions are of central concern: (1) What is the optimal number of instruments to use? (2) Should the instruments receive different weights? This paper contains the following contributions toward resolving these issues. First, I propose a kernel weighted generalized method of moments (GMM) estimator that uses a trapezoidal kernel. This kernel turns out to be attractive to select and weight the number of moments. Second, I derive the higher order mean squared error of the kernel weighted GMM estimator and show that the trapezoidal kernel generates a lower asymptotic variance than regular kernels. Finally, Monte Carlo simulations show that in finite samples the kernel weighted GMM estimator performs on par with other estimators that choose optimal instruments and improves upon a GMM estimator that uses all instruments.     

A method for determining customer requirement weights based on TFMF and TLR

‘Customer requirements’ (CRs) management plays an important role in enterprise systems (ESs) by processing customer-focused information. Quality function deployment (QFD) is one of the main CRs analysis methods. Because CR weights are crucial for the input of QFD, we developed a method for determining CR weights based on trapezoidal fuzzy membership function (TFMF) and 2-tuple linguistic representation (TLR). To improve the accuracy of CR weights, we propose to apply TFMF to describe CR weights so that they can be appropriately represented. Because the fuzzy logic is not capable of aggregating information without loss, TLR model is adopted as well. We first describe the basic concepts of TFMF and TLR and then introduce an approach to compute CR weights. Finally, an example is provided to explain and verify the proposed method.     

Modeling the lockdown relaxation protocols of the Philippine government in response to the COVID-19 pandemic: An intuitionistic fuzzy DEMATEL analysis

The COVID-19 pandemic, which started at Wuhan, has shut down world economies, prompting governments to impose drastic lockdown measures of the economy and the society. As these measures are exhausted, non-COVID-19 related issues such as those associated with the mental and physical well-being of people under lockdowns became an emerging concern. As these issues are evident, not to mention the economic downturn, governments are currently looking at designing lockdown relaxation efforts by simultaneously considering both public health and economic restart. Without documented experiences to rely on, governments are resorting to trial-and-error approach in creating a lockdown exit strategy while preventing succeeding waves of cases that may overwhelm healthcare facilities. Thus, this work pioneers the use of the decision-making trial and evaluation laboratory (DEMATEL) method with intuitionistic fuzzy (IF) sets along with the domain of public health and the emerging COVID-19 pandemic. The DEMATEL handles the intertwined causal relationships among guideline protocols for the relaxation strategy. The intuitionistic fuzzy set theory addresses the vagueness and uncertainty of human judgments in the context of the DEMATEL. A case study of the Philippine government response for the lockdown exit is presented to evaluate the applicability of the proposed method. Findings reveal that compliance of minimum public health standards, limited movement of persons, suspension of physical classes, the prohibition of mass gatherings, non-operation of category IV industries, and non-operation of hotels or similar establishments are the most crucial protocols for such strategy. These findings offer practical insights for the government to allocate resources and impose measures to ensure their implementation, as well as for developing mitigation efforts to cushion their socio-economic impacts. Policy insights and avenues for future works are also discussed.     

Intuitionistic fuzzy sets in questionnaire analysis

Fuzzy sets represent an extension of the concept of set, used to mathematically model veiled and indefinite concepts, such as those of youth, poverty, customer satisfaction and so on. Fuzzy theory introduces a membership function, expressing the degree of membership of the elements to a set. Intuitionistic fuzzy sets and hesitant fuzzy sets are two extensions of the theory of fuzzy sets, in which non-membership degrees and hesitations expressed by a set of experts are, respectively, introduced. In this paper, we apply intuitionistic fuzzy sets to questionnaire analysis, with a focus on the construction of membership, non-membership and uncertainty functions. We also suggest the possibility of considering intuitionistic hesitant fuzzy sets as a valuable theoretical framework. We apply these models to the evaluation of a Public Administration and we assess our results through a sensitivity analysis.     

基于IOWA-FAHP的物流需求组合预测模型

面向物流需求的预测问题,提出了一种基于诱导有序加权平均算子和模糊层次分析法相结合的组合预测模型。首先,采用诱导有序加权平均算子建立组合预测模型,并基于历史数据解算各单项预测模型的加权系数;然后,针对组合预测模型中各单项模型的加权系数确定问题,引入模糊层次分析法,得到各单项预测模型的公平排序,进而确定各单项预测模型在预测年的诱导值序列,从而预测出相应物流需求量;最后通过应用算例验证了该模型的正确性和可靠性。     

A fuzzy AHP approach based on the concept of possibility extent

The main purpose of this paper is to develop a fuzzy AHP method for tackling the uncertainty and imprecision existing in multi-criteria decision process. The proposed method uses fuzzy pair-wise comparison judgments in place of exact numerical values of the comparison ratios. The geometric mean technique is used to integrate all decision-makers’ opinions and construct the fuzzy positive reciprocal matrices. The algebraic operations of triangular fuzzy numbers are utilized to calculate the fuzzy suitability indices of all alternatives. The extent analysis method is used to compute the degree of possibility of priority among fuzzy suitability indices. Besides, two principles are presented to solve the multi-criteria decision problem in a fuzzy decision environment. Principle I provides a partial preorder, and Principle II gives a total preorder on the set of the possible alternatives. Finally, a numerical example of selecting the company with optimal performance in performing customer relationship management is used to demonstrate the decision process of proposed method.     

A cost evaluation method for dynamic line balancing

A procedure is presented for calculating stochastic costs, which include operator (labor) and inventory costs, associated with dynamic line balancing. Dynamic line balancing, unlike the traditional methods of assembly and production line balancing, assigns operators to one or more operations, where each operation has a predetermined processing time and is defined as a group of identical parallel stations. Operator costs and inventory costs are stochastic because they are functions of the assignment process employed in balancing the line, which may vary throughout the balancing period, and the required flow rate. Earlier studies focused on the calculation of the required number of stations and demonstrated why the initial and final inventories at the different operations are balanced.The cost minimization method developed in the article can be used to evaluate and compare the assignment of operators to stations for various assignment heuristics. Operator costs and inventory costs are the components of the cost function. The operator costs are based on the operations to which operators are assigned and are calculated for the entire work week regardless of whether an operator is given only a partial assignment which results in idle time. It is assumed that there is no variation in station speeds, no learning curve effect for operators' performance times, and no limit on the number of operators available for assignment. The costs associated with work-in-process inventories are computed on a “value added” basis. There is no charge for finished goods inventory after the last operation or raw material before the first operation.The conditions which must be examined before using the cost evaluation method are yield, input requirements, operator requirements, scheduling requirements and output requirements. Yield reflects the output of good units at any operation. The input requirement accounts for units discarded or in need of reworking. The operator requirements define the calculation of operator-hours per hour, set the minimum number of operators at an operation, and require that the work is completed. The scheduling requirements ensure that operators are either working or idle at all times, and that no operator is assigned to more than one operation at any time. The calculation of the output reflects the yield, station speed, and work assignments at the last operation on the line.An application of the cost evaluation method is discussed in the final section of the article. Using a simple heuristic to assign operators, the conditions for yield, inputs, operators, scheduling, and output are satisfied. The costs are then calculated for operators and inventories.In conclusion, the cost evaluation method for dynamic balancing enables a manager to compare the costs of assigning operators to work stations. Using this method to calculate the operator and inventory costs, a number of different heuristics for assigning operators in dynamic balancing can be evaluated and compared for various configurations of the production line. The least cost solution procedure then can be applied to a real manufacturing situation with similar characteristics.