基于多粒度语言的动态联盟合作伙伴群决策

客观事物的复杂性和人类认识的局限性使得评价指标的数据很难用一个精确数表示,具有不同程度的不确定性。在比较分析现有各种表达不确定性方法的基础上,提出了基于多粒度语言的虚拟企业合作伙伴选择方法。首先将多粒度语言一致化为标准语言评价集中的语言,然后基于正态分布的方法求位置权重向量,采用扩展的二元语义组合有序加权几何平均(ET-COWGA)算子集结各专家评价值得到群体综合的各属性评价值。根据局部优化和全局优化结果得到精确的属性权重,利用加权几何平均(ET-WGA)算子集结各属性值,得到方案的综合评价值。最后通过一个实例说明了合作伙伴选择的整个决策过程,并论证了该方法在最后优化决策过程中的有效性。     

不确定偏好信息下质量管理的含糊群体决策

为实现质量管理的定量决策和信息集结,将质量管理决策问题归结为偏好信息不确定下群体决策问题.建立了质量管理多属性群体决策模型,分析了决策中语言偏好信息和权重偏好信息的不确定性.采用双重模糊的含糊集表达决策语言的不确定性,同时将模糊集的基本运算引入到含糊集中,定义了四种处理权重偏好信息的决策函数,分别实现了质量管理决策量化结果的集结处理.比较了这些决策函数在权重偏好信息不同的情况下的集结行为,通过案例计算验证了这些决策函数对信息集结的不同效果和应用场合.     

Evolution of operator decision making

Advances in control system technology have altered the types of decision making activities performed by control operators. The changes in decision making necessitate changes in configuration of the operator-process interface to support the new tasks. Alarms and displays that were adequate for operation a few years ago may prove totally inappropriate today as the role of the operator has shifted. This paper describes the changes in decision making in terms of accepted models of operator performance and discusses the impact on alarm/display requirements.     

Selecting Plant Location via a Fuzzy TOPSIS Approach

A fuzzy TOPSIS approach for selecting plant location is proposed, where the ratings of various alternative locations under various criteria and the weights of various criteria are assessed in linguistic terms represented by fuzzy numbers. In the proposed method, the ratings and weights assigned by decision makers are averaged and normalised into a comparable scale. The membership function of each normalised weighted rating can be developed by interval arithmetic of fuzzy numbers. To avoid complicated aggregation of fuzzy numbers, these normalised weighted ratings are defuzzified into crisp values. A closeness coefficient is defined to determine the ranking order of alternative locations by calculating the distances to both the ideal and negative-ideal solutions. Using the suggested method, the decision makers’ fuzzy assessments with different rating viewpoints and the trade-off among different criteria are considered in the aggregation procedure to assure more convincing decision making. A numerical example demonstrates the feasibility of the proposed method. ID="A1"Correspondance and offprint requests to: Dr T.-C. Chu, Institute of Industrial Management, Southern Taiwan University of Technology, 1 Nan-Tai Street, Yung Kang City, Tainan County 710, Taiwan. E-mail: mrchu@mail.stut.edu.tw     

A unique fuzzy multi-criteria decision making: computer simulation approach for productive operators’ assignment in cellular manufacturing systems with uncertainty and vagueness

In today’s competitive world, manufacturing firms require to meet demand, increase quality, and decrease cost due to continuous changes in the market. Because of the importance of flexible manufacturing system, the optimum operator allocation problem in cellular manufacturing systems (CMSs) is a challenging issue. Hence, the aim of this paper is presenting a decision making approach based on Fuzzy Analytical Hierarchy Process (Fuzzy AHP), Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), and computer simulation to determine the most efficient number of operators and the efficient measurement of operator assignment in CMS. Also, the proposed approach is performed by employing the number of operators, average lead time of demand, average waiting time of demand, number of completed parts, operator utilization, and average machine utilization as criteria for decision making. An actual case is considered and a computer simulation which considers various operators layout is developed with respect to the purpose of this study and 36 scenarios is produced. In order to find the best scenarios among 36 alternatives, a combined Fuzzy AHP and TOPSIS is employed. The Fuzzy AHP method is applied to determine the importance weight of the criteria. Finally, the TOPSIS method is utilized to rank and analyze scenarios. Also, a sensitivity analysis is carried out for validating the obtained results.     

Solving a multi-objective job shop scheduling problem with sequence-dependent setup times by a Pareto archive PSO combined with genetic operators and VNS

In this paper, we present a combination of particle swarm optimization (PSO) and genetic operators for a multi-objective job shop scheduling problem that minimizes the mean weighted completion time and the sum of the weighted tardiness/earliness costs, simultaneously. At first, we propose a new integer linear programming for the given problem. Then, we redefine and modify PSO by introducing genetic operators, such as crossover and mutation operators, to update particles and improve particles by variable neighborhood search. Furthermore, we consider sequence-dependent setup times. We then design a Pareto archive PSO, where the global best position selection is combined with the crowding measure-based archive updating method. To prove the efficiency of our proposed PSO, a number of test problems are solved. Its reliability based on some comparison metrics is compared with a prominent multi-objective genetic algorithm (MOGA), namely non-dominated sorting genetic algorithm II (NSGA-II). The computational results show that the proposed PSO outperforms the above MOGA, especially for large-sized problems.     

基于主-从遗传算法求解柔性调度问题

通过分析柔性作业车间调度问题中工件与设备的特征及两者间的关系,提出了一种主一从遗传算法的调度方案。在该算法中,主、从染色体分别采用工件基因块和设备基因块的分块编码。主染色体代表可行加工路径组合,从染色体代表主染色体约束下的可行调度方案。然后,以最小化工件延迟时间为目标,为主染色体设计选择和多点变异两类遗传操作;以最小化设备空闲时间为目标,为从染色体设计选择、多点交叉和多点变异3类遗传操作。从染色体适应值取其代表的调度方案中工件流通时间的倒数,主染色体适应值取其对应从染色体种群的最优适应值。这种双层多点遗传操作避免了非可行解的产生,并可采用类似旅行商问题的遗传操作。最后,通过仿真和比较实验,验证了该算法的有效性。     

A fuzzy hybrid group decision support system approach for the supplier evaluation process

The quality and delivery performance of a typical company depends largely on the capability of its suppliers. It is therefore important for a company to evaluate the performance of its existing suppliers. However, the problem of supplier evaluation is rather complex when a group of decision makers responsible for these suppliers are geographically dispersed. Evaluating decisions requiring the elicitation of vague and imprecise linguistic information expressed in fuzzy terms. For this purpose, a hybrid fuzzy group decision-making approach for supplier evaluation is proposed, integrating the fuzzy analytic hierarchy process (F-AHP) and the fuzzy preference-ranking-organization-method-for-enrichment-of-evaluation (PROMETHEE) group decision support system (F-PROMETHEE GDSS) method. F-AHP is used to determine the weight of multiple criteria while F-PROMETHEE GDSS is applied for the final ranking of suppliers from a group decision viewpoint. The approach advances the supplier evaluation context in two aspects. First, it treats each decision maker uniquely in terms of the preference function and threshold levels. Second, it provides rapid communication between teams through video conferencing. The hybrid approach is used to evaluate the suppliers of a dairy company.     

基于形态学边缘匹配的数字稳像方法

在一些实际应用场合,摄像机设备的震动是造成视频序列失稳的重要原因,为此提出了一种基于形态学边缘匹配的数字稳像方法,该方法首先利用形态学方法提取视频图像边缘,然后利用当前帧子块与参考帧子块的边缘进行特征匹配,以确定当前帧子块相对于参考帧的局部运动矢量,同时对得到的局部运动矢量进行分析判决,以确定该局部运动矢量是否为真正的抖动偏移量,消除视频帧本身因存在局部运动目标、低对比度、纹理区域等因素对全局运动矢量估计的影响,最后通过判别确认的局部运动矢量确定全局运动矢量并进行运动补偿,实现数字稳像。仿真实验表明该方法稳像精度较高,复杂度低,实际应用稳像效果良好,可应用于因摄像头平移震动等因素造成视频序列失稳。     

Measuring batting parameters in cricket: A two-stage regression-OWA method

The selection of cricket players by team selectors and sponsors for endorsement of products is primarily dependent on the performance of players in terms of various parameters in their areas of expertise such as batting or bowling. This paper proposes a two-stage method for measuring and ranking batting parameters in cricket using ordered weighted averaging (OWA) operator and regression. The first stage measures the performance of batsmen using OWA operator followed by ranking of batting parameters using regression. The study reveals that the ranking obtained for batting parameters is not sensitive to changes in the OWA weights. A real dataset of 40 batsmen from Indian Premier League 2011 is considered for analysis purpose. Although this paper focuses only on the batting discipline the results from this paper can be extended to investigate bowling discipline using multiple parameters. These results can be implemented to enhance the quality of decision making.     

A decision support system for the selection of a rapid prototyping process using the modified TOPSIS method

As a new technology that fabricates a three-dimensional (3D) physical model from computer-aided design (CAD) data using an additive process, rapid prototyping (RP) has been developed to reduce product development time and cost. Recently, many newly emerging techniques of RP have been commercialized worldwide. This paper deals with the selection of an optimal RP system that best suits the end use of a part by using multiple-attribute decision making and the test part designed with conjoint analysis to reflect users’ preference. Evaluation factors include only the major attributes that significantly affect the performance of an RP system such as accuracy, roughness, strength, elongation, part cost and build time. Crisp values such as accuracy and surface roughness are obtained with a new test part developed in this study. The part cost and build time are identified as falling within approximate ranges due to varying costs and many variable parameters. They are presented as linguistic values that can be described with triangular fuzzy numbers. Based on the evaluation values obtained, an appropriate RP process for a specific part application can be selected using a modified technique of order preference by a similarity to ideal solution (TOPIS) method given crisp data and linguistic variables as the alternatives of attributes. Finally, each attribute’s weight is assigned using a pairwise comparison matrix. Determined using these weights, the final ranking order aids in the selection of the RP system.     

Overall equipment effectiveness when production speeds and stoppage durations are uncertain

Evaluation of manufacturing equipment performance has been very important in production-related functions such as planning, scheduling, and maintenance. Nevertheless, low accuracy of performance measurements can mislead decision makers. In this study, overall equipment effectiveness (OEE) is considered as a performance indicator of manufacturing equipment. In practice, components of OEE may consist of uncertainty due to manual or semi-automatic measurement systems. As a consequence, true performance of equipment may be masked by the uncertainty of measurements. In this study, two types of uncertainty are considered in production speed and stoppage duration measurements, which are used in calculating OEE components. When the measurements have uncertainty due to use of linguistic terms or some minor stoppages, idling, or speed losses being ignored, fuzzy arithmetic is used as a method to handle uncertainty. In some low accuracy cases, best guess interval estimates of operators may better reflect the state than just providing a point estimate. For such cases, interval arithmetic is used as a method to handle uncertainty. Implementation of the methods are illustrated using two real-world examples and a software is provided for practitioners. Proposed methods help making better informed decisions using OEE under measurement uncertainty of production speed and stoppage durations.     

Dynamic gesture recognition using signal processing based on fuzzy nominal scales

During the conversion of the state of a physical entity to an information entity the measurement process preserves a part of the properties of the set of physical states. The set of the preserved properties depends on the initial set of properties and on the scale used for the measurement. It defines the set of relations and operators than can be applied to information entities. This means that the measurement scale induces the set of operators that can be used for signal processing. This paper presents some characteristics of fuzzy nominal scales, more specifically the existence of a distance operator on such scales. Numerical data provided by a data glove are transformed into linguistic data with fuzzy nominal scales. Then the processing of linguistic signals measured with a fuzzy nominal scale is presented. Finally the linguistic data given by the glove are then processed to recognize dynamic hand gestures.     

基于改进TOPSIS法的液压系统维修决策

针对液压系统故障原因隐蔽、维修决策困难的问题,引入并改进了传统的逼近理想值排序(TOPSIS)法。通过提出绝对理想解概念,使TOPSIS法具有强保序性,消除了影响决策的逆序问题;利用马氏距离代替欧氏距离,克服了量纲不同对距离计算的影响,同时降低了对指标数据的要求,提高了决策的可靠性。最后,将改进后的TOPSIS法应用于汽车起重机支腿液压回路的维修决策,并与改进前的方法对比,验证了该方法在液压系统维修决策中的有效性。     

基于模糊效用值排序的模糊层次分析法在机械运动方案优选中的应用

为了有效地对机械运动方案进行优选决策,在层次分析法的基础上,引入群决策方法和模糊效用值排序理论,提出一种基于三标度法的群体多准则模糊层次分析法。在多人决策情况下,首先利用简化的三标度法直接生成一致性的判断矩阵,在充分考虑决策者和决策对象不确定性的同时,将群体意见集成到三角模糊数中,最后通过模糊数总效用值排序获得各方案优先顺序。实例表明,该方法简化了分析过程,同时又综合了群体的意见,从而为机械运动方案优选提供了一种实用化方法。     

<Emphasis Type="Italic">A Fuzzy TOPSIS Method for Robot Selection</Emphasis>

A fuzzy TOPSIS method for robot selection is proposed, where the ratings of various alternatives versus various subjective criteria and the weights of all criteria are assessed in linguistic terms represented by fuzzy numbers. The values of objective criteria are converted into dimensionless indices to ensure compatibility between the values of objective criteria and the linguistic ratings of subjective criteria. The membership function of each weighted rating is developed by interval arithmetic of fuzzy numbers. To avoid complicated aggregation of fuzzy numbers, these weighted ratings are defuzzified into crisp values by the ranking method of mean of removals. A closeness coefficient is defined to determine the ranking order of alternatives by calculating the distances to both the ideal and negative- ideal solutions. A numerical example demonstrates the computational process of the proposed method. ID="A1"Correspondance and offprint requests to: Dr T.-C. Chu, Department of Management and Information Technology, Southern Taiwan University of Technology, 1 Nan-Tai Street, Yung-Kang City, Tainan County 710, Taiwan. E-mail: mrchu@mail.stut.edu.tw     

基于不完全互惠偏好关系的产品工业设计方案决策

为解决产品工业设计方案决策中的偏好缺失问题,引入不完全互惠偏好关系,提出了产品工业设计方案决策流程.研究了不完全互惠偏好关系的基本理论、运算法则与缺失偏好处理算法,并据此确定产品方案偏好矩阵的一致性权重,借助层次分析法获取决策者信任权重,建立共识度模型评判决策群体偏好一致性,根据不完全互惠偏好关系一致性权重和决策群体信...     

理想解法的改进及其在工程材料综合评价中的应用

用垂直距离代替欧氏距离,并对垂直距离加权,对传统理想解法进行了改进;并以航空航天用电绝缘材料的选择为例,从功能性角度出发,选择了8个评价指标,运用改进后的理想解法对5种经过初选的候选材料进行了综合评价。结果表明:石英玻璃的加权垂直距离最小,是最佳的候选材料,评价结果正确;改进后的理想解法不仅解决了传统方法的不足,而且更好地体现了不同候选材料的优劣差异,物理含义更加明确,分析问题更全面、客观,是工程选材的一种工具。     

A general fuzzy TOPSIS model in multiple criteria decision making

Decision making is the process of finding the best option among the feasible alternatives. In classical multiple criteria decision-making (MCDM) methods, the ratings and the weights of the criteria are known precisely. Owning to vagueness of the decision data, the crisp data are inadequate for real-life situations. Since human judgments including preferences are often vague and cannot be expressed by exact numerical values, the application of fuzzy concepts in decision making is deemed to be relevant. In this paper, we proposed the application of a fuzzy distance formula in order to compute a crisp value for the standard deviation of fuzzy data. Then, we use this crisp value of the standard deviation to normalize the fuzzy data using the distance formula again. In our normalization approach, we have enough flexibility to consider various types of fuzzy numbers (such as triangular, trapezoidal, and interval). Finally, we use the technique for order preference by similarity to an ideal solution to determine the ranking order of the alternatives. A numerical example from the literature is solved to demonstrate this applicability of the proposed model. We also compare our proposed approach with similar methods in the literature using some examples with known results and a number of randomly generated test problems. The results point to the applicability of our method and signify its effectiveness in identifying solutions.     

基于量子力学的均值滤波

量子计算和量子信息是涉及物理学、计算机科学、数学以及信息科学等多个学科的新兴综合性交叉学科,有着广阔的前景。根据量子信息处理理论,提出了一种基于量子力学的自适应均值滤波方案。在提出的均值滤波中,移动的窗口图像像素采用量子叠加态表示,通过由窗内像素的特征生成的测量算子对窗口图像的作用来调整均值运算窗口的权值,进而实现基于量子力学的均值滤波。计算机仿真表明,所提出的均值滤波器与传统均值滤波器相比具有更好的滤波效果。