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The performance of distributed computing systems is partially dependent on configuration parameters recorded in configuration files. Evolutionary strategies, with their ability to have a global view of the structural information, have been shown to effectively improve performance. However, most of these methods consume too much measurement time. This paper introduces an ordinal optimization based strategy combined with a back propagation neural network for autotuning of the configuration parameters. The strategy was first proposed in the automation community for complex manufacturing system optimization and is customized here for improving distributed system performance. The method is compared with the covariance matrix algorithm. Tests using a real distributed system with three-tier servers show that the strategy reduces the testing time by 40% on average at a reasonable performance cost. 相似文献
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为进一步提高Web服务查询的准确度,找到符合用户需求的服务,查询结果不仅要与查询描述内容近似,还应具有一定的结构近似性。该文提出一种具有高级查询描述能力的Web服务查询方法,与以往单纯的内容描述相比增加了对结构的描述,并在结构查询描述中引入通配符以增加结构描述的灵活性,提高结果命中率。根据基于WSDL描述的Web服务的组织结构特点,将Web服务建模为无序标签树,并给出带通配符的无序树松弛匹配算法模型。该算法能在多项式时间内完成计算,经测试运行时间在ms级,并且查询描述中通配符的数目对运行时间基本没有影响。 相似文献
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In this paper, we study the problem of rule extraction from data sets using the rough set method. For inconsistent rules due to improper selection of split-points during discretization, and/or to lack of information, we propose two methods to remove their inconsistency based on irregular decision tables. By using these methods, inconsistent rules are eliminated as far as possible, without affecting the remaining consistent rules. Experimental test indicates that use of the new method leads to an improvement in the mean accuracy of the extracted rules. 相似文献
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供需链系统的协调机制与风险分配 总被引:5,自引:0,他引:5
为了研究供需链系统的协调机制对系统风险分配的影响,提出了一种系统风险的量化方法.使用该方法证明了供需链达到协调状态时,回购策略下供需双方风险不变;双边价格策略下,供需链上下游总有一方风险为零,另一方承担系统全部风险;而目标减免折扣策略下销售商风险始终大于供需链系统风险.结合对经典合同策略的分析,提出了一种新的策略形式,不但能够协调供需链系统,而且可将利润与风险在供需双方任意分配. 相似文献
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处理带约束的多目标优化进化算法 总被引:29,自引:0,他引:29
针对当前对求解多目标优化的遗传算法中主要考虑如何处理相互冲突的多个目标间的优化,而很少考虑对约束条件的处理的问题,提出一种求解带约束的多目标优化遗传算法,利用邻域比较与存档操作遗传算法处理多个相互冲突的目标之间的优化、利用不可行度选择操作处理约束条件和选用约束主导原理指导进化过程选择操作; 面向多目标约束优化算法,列举了2个难点典型问题进行仿真计算研究,仿真结果表明该算法能较大概率地获得多目标约束优化问题的可行Pareto最优解. 相似文献
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Introduction A flow shop is a manufacturing system where n jobs are processed on m machines and each job has the same machine-order[1]. If the job-order on each ma- chine is also the same, it is a permutation flow shop, in which some job-sequences can be … 相似文献
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一种基于目标规划的AHP参数学习算法 总被引:4,自引:0,他引:4
为提高采用层次分析(AHP)算法辅助采购决策问题的准确性,针对用户的最终选择与模型推荐结果的不一致,该文采用目标规划方法对AHP模型参数权重进行学习。通过理论分析和实例说明了算法的可行性,并将算法初步应用于某摩托车电子商务平台供应商选择决策支持系统。这种基于目标规划的AHP参数学习算法可通过多次学习积累采购者的评价习惯,弥补行业性电子商务平台一般性决策支持工具的不足,也可以用于其它决策支持领域相近问题。 相似文献