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121.
图的可达性查询被广泛应用于生物网络、社会网络、本体网络、RDF网络等.由于对数据操作时引入的噪声和错误使这些图数据具有不确定性,而确定图的可达查询不能有效地处理不确定性,因此该文研究用概率语义描述的图可达性查询.具体的,该文使用可能世界概率模型定义不确定图(称为概率图),基于该模型,研究了基于阈值的概率可达查询(T-PR).首先为避免枚举所有可能世界,给出一个基本算法可精确求解T-PR查询.其次为进一步加速基本算法,给出3种改进方法,它们是不确定事件界、同构图的缩减、基于不相交路径和割集的界.通过合理的组合给出3种方法的合并算法.最后基于真实概率图数据的大量实验验证了该文的设计. 相似文献
122.
负载划分是决定集群计算环境下基于复杂网络的并行社会学仿真性能的核心因素之一.由于背景负载等因素的影响,集群系统中往往需要根据实际可用计算资源非均匀分配仿真任务,而现有针对无标度特性拓扑结构的并行仿真负载划分算法无法适应集群环境下计算负载非均匀划分的需求.针对这一问题,提出了一个基于集散节点聚合的负载划分算法,将集群计算... 相似文献
123.
Recovery of sensor embedded washing machines using a multi-kanban controlled disassembly line 总被引:1,自引:0,他引:1
Product recovery involves the recovery of materials and components from returned or end-of-life products. Disassembly, an element of product recovery, is the systematic separation of an assembly into its components, subassemblies or other groupings. Stricter environmental regulations together with dramatic decrease in natural resources and landfills have increased the importance of disassembly as all product recovery options require some level of disassembly. Due to changes made during the lifetime of a product by customers or service personnel, the number and the version of components prior to disassembly is unknown. Customers may also discriminate between and demand different versions of components. The existence of non-functional components further adds to the uncertainty associated with disassembly yield. Sensors implanted into products during their production can address this uncertainty by providing information on the number, condition and version of components prior to disassembly. In this study, we evaluate the impact of sensor embedded products (SEPs) on the various performance measures of a washing machine (WM) disassembly line controlled by a multi-kanban system, which takes into consideration the highly stochastic behavior of the line while managing material and kanban flows. First, separate design of experiments studies based on orthogonal arrays are performed for conventional products and SEPs. In order to observe the response of each experiment, detailed discrete event simulation (DES) models for both types of products are developed considering the precedence relationships among the components of a WM. Then, pair-wise t-tests are conducted to compare the two cases based on different performance measures. According to the results, SEPs provide significant reductions in all costs (viz., backorder, holding, disassembly, disposal, testing and transportation) while increasing revenue and profit. 相似文献
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125.
This paper focuses on the performance evaluation of complex man-made systems, such as assembly lines, electric power grid,
traffic systems, and various paper processing bureaucracies, etc. For such problems, applying the traditional optimization
tool of mathematical programming and gradient descent procedures of continuous variables optimization are often inappropriate
or infeasible, as the design variables are usually discrete and the accurate evaluation of the system performance via a simulation
model can take too much calculation. General search type and heuristic methods are the only two methods to tackle the problems.
However, the “goodness” of heuristic methods is generally difficult to quantify while search methods often involve extensive
evaluation of systems at many design choices in a large search space using a simulation model resulting in an infeasible computation
burden. The purpose of this paper is to address these difficulties simultaneously by extending the recently developed methodology
of Ordinal Optimization (OO). Uniform samples are taken out from the whole search space and evaluated with a crude but computationally
easy model when applying OO. And, we argue, after ordering via the crude performance estimates, that the lined-up uniform
samples can be seen as an approximate ruler. By comparing the heuristic design with such a ruler, we can quantify the heuristic
design, just as we measure the length of an object with a ruler. In a previous paper we showed how to quantify a heuristic
design for a special case but we did not have the OO ruler idea at that time. In this paper we propose the OO ruler idea and
extend the quantifying method to the general case and the multiple independent results case. Experimental results of applying
the ruler are also given to illustrate the utility of this approach.
Zhen Shen received the B.E. degree from Department of Automation, Tsinghua University, Beijing, China in 2004. Currently, he is a Ph.D. candidate of Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University. He was a Visiting Scholar from Oct. 2007 to Apr. 2008 at Department of Manufacturing Engineering and Center for Information and Systems Engineering, Boston University, MA, USA. He specializes in the area of the discrete event dynamic systems (DEDS) theory and applications, and the optimization of complex systems. He is a student member of IEEE. Yu-Chi Ho received his S.B. and S.M. degrees in Electrical Engineering from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Except for three years of full time industrial work he has been on the Harvard faculty. Since 1969 he has been Gordon McKay Professor of Engineering and Applied Mathematics. In 1988, he was appointed to the T. Jefferson Coolidge Chair in Applied Mathematics and Gordon McKay Professor of Systems Engineering at Harvard and as visiting professor to the Cockrell Family Regent’s Chair in Engineering at the University of Texas, Austin. In 2001, he retired from teaching duties at Harvard and became a Research Professor (2001–2006) and also was appointed to be a chair professor and chief scientist (part time), at the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing China. Qian-Chuan Zhao received the B.E. degree in automatic control in July 1992, the B.S. degree in applied mathematics in July 1992, and the Ph.D. degree in control theory and its applications in July 1996, all from Tsinghua University, Beijing, China. He is currently a Professor and Associate Director of the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University. He was a Visiting Scholar at Carnegie Mellon University, Pittsburgh, PA, and Harvard University, Cambridge, MA, in 2000 and 2002, respectively. He was a Visiting Professor at Cornell University, Ithaca, NY, in 2006. His research interests include discrete event dynamic systems (DEDS) theory and applications, optimization of complex systems, and wireless sensor networks. Dr. Zhao is an associate editor for the Journal of Optimization Theory and Applications. 相似文献
Zhen ShenEmail: |
Zhen Shen received the B.E. degree from Department of Automation, Tsinghua University, Beijing, China in 2004. Currently, he is a Ph.D. candidate of Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University. He was a Visiting Scholar from Oct. 2007 to Apr. 2008 at Department of Manufacturing Engineering and Center for Information and Systems Engineering, Boston University, MA, USA. He specializes in the area of the discrete event dynamic systems (DEDS) theory and applications, and the optimization of complex systems. He is a student member of IEEE. Yu-Chi Ho received his S.B. and S.M. degrees in Electrical Engineering from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Except for three years of full time industrial work he has been on the Harvard faculty. Since 1969 he has been Gordon McKay Professor of Engineering and Applied Mathematics. In 1988, he was appointed to the T. Jefferson Coolidge Chair in Applied Mathematics and Gordon McKay Professor of Systems Engineering at Harvard and as visiting professor to the Cockrell Family Regent’s Chair in Engineering at the University of Texas, Austin. In 2001, he retired from teaching duties at Harvard and became a Research Professor (2001–2006) and also was appointed to be a chair professor and chief scientist (part time), at the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing China. Qian-Chuan Zhao received the B.E. degree in automatic control in July 1992, the B.S. degree in applied mathematics in July 1992, and the Ph.D. degree in control theory and its applications in July 1996, all from Tsinghua University, Beijing, China. He is currently a Professor and Associate Director of the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University. He was a Visiting Scholar at Carnegie Mellon University, Pittsburgh, PA, and Harvard University, Cambridge, MA, in 2000 and 2002, respectively. He was a Visiting Professor at Cornell University, Ithaca, NY, in 2006. His research interests include discrete event dynamic systems (DEDS) theory and applications, optimization of complex systems, and wireless sensor networks. Dr. Zhao is an associate editor for the Journal of Optimization Theory and Applications. 相似文献
126.
127.
针对网格仿真中的事件调度问题,提出一种新的时序管理方法。该方法同时考虑网格仿真成员的按需模型服务调用与成员间的交互,对仿真中具体存在的事件进行分类,建立成员的相关局部事件触发矩阵和时序关系矩阵,并应用Mutli-AWS算法求解每个事件的开始时间。实验结果证明,该方法可以确保成员之间事件的时序关系,有效解决成员按需模型服务调用问题。 相似文献
128.
以发布/订阅范型在时间维度上解耦导致的不确定性为出发点,采用时序分析方法,研究范型中信息投递的可靠性保障。在定义投递信息可用性的基础上,给出保证信息向订阅者可靠投递系统应满足的基本计算条件,探讨底层通信设施对可靠性的影响。针对发布/订阅范型中信息可靠投递的问题,提出必要的计算条件。分析结果表明,信息的可靠投递与订阅活跃期、订阅延迟、发布传播延迟密切相关。 相似文献
129.
130.
复杂事件处理技术是射频识别技术(Radio Frequency Identification,RFID)应用中的重要技术。现有的RFID复杂事件处理模型,例如基于petri网的模型、基于树的模型、基于图的模型、基于自动机的模型,并不能十分有效地解决复杂的RFID应用问题,具体地说,RFID复杂事件的语义分析方面缺乏进一步的研究。针对上述问题,提出了一种RFID复杂事件语义分析方法。该方法,借鉴编译原理中的语义分析技术,为事件增添定义了继承属性和综合属性,同时按照事件之间的关系,定义了三种语义模式,最后通过一个语义解析算法,解析出了特定模式组合的语义信息。实验证实,该方法取得了比较理想的效果。 相似文献