模糊权重约束的DEA模型及其应用

基于Zadeh模糊优越集定义,应用模糊权重约束DEA模型对医院服务效率进行评价.通过最大化模糊隶属函数来确定投入与产出权重的上限和下限,以避免传统DEA模型中权重为0的缺陷.实例选取期末实有床位数和医护人员数为两个投入变量,总诊疗人次和总出院人次为两个产出变量,评价广州市15所医院的相对服务效率.评价结果对医院管理决策更具客观性和实用性.     

Research on Evaluating the Efficiency of the Project Financing of the Energy Service Company

The financing efficiency evaluation of the ESCO (Energy Service Company) is an important approach to improve the operation efficiency of existing building energy-saving projects. To scientifically and reasonably evaluate the financing efficiency of the ESCO, this paper puts forward a combination evaluation model based on the method set. Firstly, the method set is composed of different methods that meet the demand of statistical coherence, and KENALL-W coefficient test of concordance is used to check up the coherence of the ranking results of the different methods. Secondly, mean, Borda and Copeland are used separately for calculating the combination evaluation results and the circular combination method is used to ensure the coherence of evaluation results. Finally, the combination evaluation model is used to evaluate the 10 ESCO business project financing benefits, and the effectiveness of the models is verified accordingly.     

基于改进的TOPSIS法与RSR法的质量改善项目综合评估

针对失效模式与影响分析中的风险优先数（RPN）方法在质量改善项目排序问题上的局限性,提出一种新的排序方法。首先,借助模糊集理论和熵权法,确定决策指标的模糊指标值和主、客观权重;随后采用改进的理想解逼近法（TOPSIS）与秩和比法（RSR）获得优先级排序和分档;同时,提出并定义了相对应的关键术语：改善主题、难易程度、发生度和改善潜力,最后,结合企业实例验证了新排序方法的有效性和稳定性。     

基于DEA的制造系统全要素能源效率评价与优化

针对目前机械加工车间制造系统能源效率评价需要基于大量的机械加工试验来分析能量消耗,需要基于经验公式来获得能源效率指标,以及没有实现基于能效评价后的能效优化等问题,基于生产管理信息系统监测数据,提出一种制造系统全要素能源效率评价指标。用数据包络分析方法对机械加工车间制造系统全要素能源效率进行评价,使用能源效率优化分析方法构建能源效率函数关系,从而提出降低能耗和提高能源利用率的定量科学方法。最后以某变速箱装配车间为例,通过实例分析,验证该评价及优化方法的理论及应用价值。     

Relationships between solid waste management performance and environmental practice adoption in Welsh small and medium-sized enterprises (SMEs)

For small and medium-sized manufacturing enterprises (SMEs), the determination of whether the adoption of environmentally supportive practices relates to good environmental performance has only been scarcely investigated. By using an empirical sample of 299 Welsh SMEs, this paper investigates just this issue. SMEs that have adopted five environmental practices and those that have not are compared as well as their environmental and economic performance using solid waste management activities. The results show that those organizations that have not adopted these practices perform better on environmental performance measures. The explanation, for what seems like a counterintuitive result, may be due to a reactive adoption of these practices to help mitigate poor performance on solid waste management practices. Additional insights and managerial implications are presented since these results will help identify methods to aid SMEs further in the adoption of environmentally supportive practices.     

基于混沌差分进化粒子群算法的模糊资源受限项目调度问题

本文研究了工期模糊情况下的资源受限项目调度问题,采用一种基于区间数距离的模糊取最大运算比较模糊工期的大小,解决了以往研究中忽略的工期模糊情况下,项目关键路径可能会发生改变,相应地各活动的模糊调度时间以及项目的模糊最短工期也可能随之发生改变的问题。引入一种基于混沌和差分进化的混合粒子群优化算法,并对算法的惯性权重进行改进来求解上述问题。通过一个算例验证了所建立模型及提出方法的有效性。     

DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection

Data envelopment analysis (DEA) has been extended to cross-efficiency evaluation to provide better discrimination and ranking of decision-making units (DMUs). However, the non-uniqueness of optimal weights in the traditional DEA models (CCR and BCC models) has reduced the usefulness of the DEA cross-efficiency evaluation method. To solve this problem, we introduce the concept of the satisfaction degree of a DMU towards a set of optimal weights for another DMU. Then, a new DEA cross-efficiency evaluation approach, which contains a maxmin model and two algorithms, is proposed based on the satisfaction degrees of the DMUs. Our maxmin model and algorithm 1 can obtain for each DMU an optimal set of weights that maximises the least satisfaction degrees among all the other DMUs. Further, our algorithm 2 can then be used to guarantee the uniqueness of the optimal weights for each DMU. Finally, our approach is applied to a real-world case study of technology selection.     

基于DEA和SD的区域物流有效性评价及优化研究

从区域物流的物流供给与物流需求等指标入手,构建了广西北部湾区域物流的数据包络分析与系统动力学的评价与改进模型,用此模型分析评价北部湾区域物流的发展现状并对未来发展趋势进行了预测与分析。根据DEA分析出的松弛变量对投入要素进行多次的试验分析,结果表明在实际操作中不一定能够达到理想的相对有效状态,但适当地改变投入要素的输入比例可以达到改善原有问题的目的。将原始物流供需比与理想供需比对比分析,结果表明理想的物流供需比例可以作为北部湾未来物流业的发展参考依据。     

基于DEA的玩性人格与团队创新行为效率研究

评价不同企业员工玩性人格对团队创新行为效率的影响程度。针对创新行为多方面输出、玩性人格多种类输入的特点,使用层次分析法（AHP）转化多种因素成相应的综合指标;利用数据包络分析（DEAP、编程排序）评价各个企业的综合创新行为效率。结果表明：长安、格力、海能达、华宇四个企业玩性人格控制较好,其他企业都处于规模报酬递增状态。在此基础上,以长安汽车作为标杆企业,对其他企业玩性人格的影响行为提出合理的对策,提高企业的创新行为     

利用对数极坐标的快速水平集算法

针对传统水平集算法计算效率低的缺点,提出了基于对数极坐标的快速水平集算法。该算法首先将均匀采样的图像映射到对数极坐标系下,再进行水平集演化运算,从而实现减少数据量、提高算法执行效率的目的,并对直接法、窄带法以及本方法的计算速度作了对比,实验结果表明,在同样获得理想分割结果的情况下,本方法分割尺寸为128×128,256×256,512×512的图像所用时间分别为0.751min,1.549min和6.113min,其计算速度要远快于另外两种方法。     

基于模糊粗糙集和鲸鱼优化支持向量机的化工过程故障诊断

针对化工过程复杂,故障数据量大、属性多,难以保证故障诊断准确率和速度的问题,提出了一种基于模糊粗糙集(fuzzy rough sets,FRS)和鲸鱼优化的支持向量机(support vector machine,SVM)的化工过程故障诊断方法.通过对化工过程历史数据分析,判别故障类型.首先,利用模糊粗糙集对离散化后的...     

工程项目多目标协同优化研究

将微粒群算法(particle swarm optimization,PSO)引入工程项目多目标协同优化领域,研究工程项目的质量、费用、资源和工期的协同优化问题。文章首先系统介绍微粒群算法原理、流程以及算法的改进发展,然后研究了工程项目质量、费用、工期和资源的协调功效系数,并建立了质量、费用、工期和资源的多目标协同优化模型,接下来介绍了应用微粒群算法编码解决工程项目多目标优化的方法步骤。最后,通过一个应用实例,计算表明微粒群算法可以准确快速地解决工程项目多目标协同优化问题。     

An extended CREAM model based on analytic network process under the type-2 fuzzy environment for human reliability analysis in the high-speed train operation

Human error is one of the largest contributing factors to unsafe operation and accidents in high-speed train operation. As a well-known second-generation human reliability analysis (HRA) technique, the cognitive reliability and error analysis method (CREAM) has been introduced to address HRA problems in various fields. Nevertheless, current CREAM models are insufficient to deal with the HRA problem that need to consider the interdependencies between the Common Performance Conditions (CPCs) and determine the weights of these CPCs, simultaneously. Hence, the purpose of this paper is to develop a hybrid HRA model by integrating CREAM, the interval type-2 fuzzy sets, and analytic network process (ANP) to overcome this drawback. Firstly, the interval type-2 fuzzy sets are utilized to express the highly uncertain information of CPCs. Secondly, the ANP is incorporated into the CREAM to depict the interdependencies between the CPCs and determine their weights. Furthermore, human error probability (HEP) can be calculated based on the obtained weights. Finally, an illustrative example of the HRA problem in high-speed train operation is proposed to demonstrate the application and validity of the proposed HRA model. The results indicate that experts prefer to express their preferences by fuzzy sets rather than crisp values, and the interdependences between the CPCs can be better depicted in the proposed model.     

基于改进田口方法的轮毂装配过程质量控制研究

针对风力机轮毂装配工序的质量控制问题，结合多品种小批量生产模式的特点，提出了一种面向定位布置的轮毂装配关键工序识别与监控的方法。综合考虑轮毂装配生产中的成本因素及相对质量损失，制定装配工序的质量特性损失标准，采用改进的质量损失函数识别轮毂装配关键工序；为解决统计过程控制（SPC）方法应用于小批量生产模式的瓶颈，引入基于直觉模糊集的工序相似性分析与评定方法，通过分析工序相似性的影响因素，构建轮毂装配成组工序相似性评判指标体系及评定模型，完成工序相似性的测度。最终使用SPC方法监控管理轮毂装配关键工序，确保轮毂的装配质量。该研究为小批量生产模式中运用SPC方法管理过程质量提供了理论依据。