敏捷供需链管理系统的可重构性研究

为快速适应供需链的需求变化 ,支持供需链系统的有效运作 ,在分析供需链特征的基础上 ,采用面向对象的方法 ,将供需链中的共性抽象为对象、过程、单元、实体、代理等不同粒度与层次的系统构件。基于系统构件 ,针对一般需求 ,建立了由系统仿真与决策 ,计划、协调、调度与控制 ,过程管理等构成的敏捷供需链管理系统 ( ASCMS)的参考系统。根据特定需求 ,通过对参考系统进行不同粒度、不同应用范围、不同开发阶段的调整或重构 ,可以有效地使 ASCMS快速满足特定需求 ,实现系统与环境同步。     

敏捷供需链中的准时采购计划方法研究

针对敏捷供需链的管理需求 ,在引入准时化 ( JIT)思想的基础上 ,就如何解决向供应商采购 ,提出了敏捷供需链中的准时采购计划问题 ,并给出了问题的数学描述。利用数学推导 ,将所建的原始优化模型转化成线性规划问题。计算结果表明 ,提出的准时采购计划方法 ,完全可以做到在供应能力平衡的前提下 ,实现敏捷供需链面向客户准时供应的经营目标 ,使提前 /拖期惩罚费用总额极小化。     

沥青混凝土路面摊铺找平方式探讨

介绍了沥青混凝土摊铺的基本要求、准备工作,对摊铺机各部件的工作原理、找平方式进行了叙述,给施工操作提供了一些具体方法,以提高沥青混凝土的摊铺质量。     

具有噪声鲁棒性的三维磁性纳米粒子成像快速重构方法

为提升磁性纳米粒子三维成像和重构速度,降低三维重构对采样投影数据完备性要求,针对含噪声投影数据三维重构优化问题,本文提出了一种具有噪声鲁棒性的三维磁性纳米粒子成像快速重构方法（noise-robust 3D sparse sampling magnetic particle imaging,3D NRSS-MPI）. 该算法通过求解一个由MPI投影成像正向模型l₂范数和稀疏正则约束建立的凸优化问题实现3D MPI图像重构. 模型不受MPI扫描轨迹限制,为不断发展的MPI新技术提供了普适性的基础模型;建立的三维全变分稀疏算子（3D total variation sparse operator, 3D TV Sparse Operator）利用MPI先验信息提升含噪MPI投影数据三维重构的鲁棒性,且可以进行无矩阵运算,大幅提升了运算效率. 通过点源和冠状血管模型成像实验表明,在1/4欠采样下,本文3D NRSS-MPI方法可以有效消除重构图像星状伪影,获取较高的图像信噪比,同时冠状动脉重建结构相似性超过0.701,可以准确地对欠采样、有噪声的MPI数据进行快速而稳健的重建,有效缩短了4倍成像和重构时间.      

拟法锥条件下带均衡约束多目标规划问题的同伦方法

利用组合同伦内点法给出了带均衡约束的多目标规划的求解问题,在合适的假设条件下,证明了该算法具有全局收敛性,数值例子表明该算法是合理有效的.     

生物降解三元共混材料聚乳酸/淀粉/聚乙烯的研制

采用具有优异降解性能的聚乳酸与淀粉、聚乙烯进行共混复合,以期得到加工性、力学性能、生物降解性优良的生物降解塑料、同时对其共混均匀性,熔体流动性,力学性能等进行了研究.     

多效唑对冬小麦的生物效应

通过喷施和根灌多效唑试验，发现冬前、单棱期、二棱期施用多效唑都能缩短基部第一、二节间长度，增加茎壁厚度、机械组织厚度和维管束数目．提高植株抗倒伏能力．施用多效唑能增加穗粒数降低粒重；在对照发生倒伏情况下表现增产效果，但在对照正常生长情况下，没有增产作用，而根灌处理还有减产趋势．     

短序落葵薯根多糖提取工艺及其生物活性

通过正交试验研究短序落葵薯根多糖水提过程中提取温度、提取时间和料液比对多糖得率的影响,采用苯酚-硫酸法对多糖进行含量测定,选出较为理想的提取条件,即加20倍水,在100℃下浸提4h,得率15.72%.短序落葵薯根多糖能有效清除活性氧,对·OH,O2-,DPPH·的半清除率IC50分别为2.89,1.99和1.89mg/mL;对脂质过氧化的半抑制率为0.038mg/mL;在还原力的测定中,1mg/mL多糖在700nm下吸光值为0.696 7.     

A message-driving formalism for modeling and simulation of multi-agent supply chain systems

To acquire a competitive advantage in the expanding market, manufacturing enterprises should be able to manage their supply chains as effectively as possible. It is now becoming popular to model supply chains as multi-agent systems and use discrete event simulation to learn more about their behaviors or investigate the implications of alternative configurations. In order to enhance the computational efficiency and keep the simulation credibility, this paper proposes a message-driving formalism for the simulation of multi-agent supply chain systems. Through the message-driving formalism, the problem of shared variables is addressed and the parallel operation of agents is implemented. Simulation experiments with a prototype implementation show that the message-driving formalism is able to provide credible results in significantly less simulation time.     

A Novel Incremental Mining Algorithm of Frequent Patterns for Web Usage Mining

Because data warehouse is frequently changing, incremental data leads to old knowledge which is mined formerly unavailable. In order to maintain the discovered knowledge and patterns dynamically, this study presents a novel algorithm updating for global frequent patterns-IPARUC. A rapid clustering method is introduced to divide database into n parts in IPARUC firstly, where the data are similar in the same part. Then, the nodes in the tree are adjusted dynamically in inserting process by ＂pruning and laying back＂ to keep the frequency descending order so that they can be shared to approaching optimization. Finally local frequent itemsets mined from each local dataset are merged into global frequent itemsets. The results of experimental study are very encouraging. It is obvious from experiment that IPARUC is more effective and efficient than other two contrastive methods. Furthermore, there is significant application potential to a prototype of Web log Analyzer in web usage mining that can help us to discover useful knowledge effectively, even help managers making decision.