To wait or not to wait: Optimal ordering under lead time uncertainty and forecast updating

There has been a dramatic increase over the past decade in the number of firms that source finished product from overseas. Although this has reduced procurement costs, it has increased supply risk; procurement lead times are longer and are often unreliable. In deciding when and how much to order, firms must consider the lead time risk and the demand risk, i.e., the accuracy of their demand forecast. To improve the accuracy of its demand forecast, a firm may update its forecast as the selling season approaches. In this article we consider both forecast updating and lead time uncertainty. We characterize the firm's optimal procurement policy, and we prove that, with multiplicative forecast revisions, the firm's optimal procurement time is independent of the demand forecast evolution but that the optimal procurement quantity is not. This leads to a number of important managerial insights into the firm's planning process. We show that the firm becomes less sensitive to lead time variability as the forecast updating process becomes more efficient. Interestingly, a forecast‐updating firm might procure earlier than a firm with no forecast updating. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

What you should know about approximate dynamic programming

Approximate dynamic programming (ADP) is a broad umbrella for a modeling and algorithmic strategy for solving problems that are sometimes large and complex, and are usually (but not always) stochastic. It is most often presented as a method for overcoming the classic curse of dimensionality that is well‐known to plague the use of Bellman's equation. For many problems, there are actually up to three curses of dimensionality. But the richer message of approximate dynamic programming is learning what to learn, and how to learn it, to make better decisions over time. This article provides a brief review of approximate dynamic programming, without intending to be a complete tutorial. Instead, our goal is to provide a broader perspective of ADP and how it should be approached from the perspective of different problem classes. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

低开销的软错误免疫寄存器设计

随着工艺尺寸的逐渐缩小,集成电路中由放射性粒子引起的软错误不断增加,在设计时必须考虑由软错误引起的可靠性问题.使用软错误免疫寄存器对电路敏感部分选择性加固是降低逻辑电路软错误率简单有效的方法.总结了常用的软错误免疫寄存器结构,并使用可靠性分析方法对8种寄存器进行量化研究和比较,得出双模时空冗余寄存器具有更高的可靠度;针对现有可靠寄存器开销较大的缺点,设计了一种基于时钟延时的动态主级时空双模冗余寄存器--DMTS-DR,不仅能很好地免疫自身的SEU,还能对前级组合逻辑的SET进行有效屏蔽.与其它可靠寄存器相比,DMTS-DR的面积和延时开销都有大幅降低,在可靠性、面积和速度间实现了较好的折中.     

炮控伺服系统自抗扰控制器优化设计

针对自抗扰控制器参数难于整定的问题,给出了一种基于自适应变异粒子群优化算法的炮控伺服系统自抗扰控制器优化设计方法.该算法结构简单,具有良好的全局收敛性,充分发挥了自抗扰控制器的控制性能.通过对某炮控伺服系统的仿真研究,表明了该设计方法的有效性.     

基于多视点的武器装备体系需求建模

简要分析了国内外武器装备体系需求研究的现状,总结了武器装备体系需求特点,基于视点的需求开发方法,给出了武器装备体系需求的需求视点,建立了武器装备体系需求建模的过程模型,提出了基于UML元语言的一致性检验方法,为构建我军一体化联合作战的武器装备体系做出了探索性的研究.     

基于任意分布随机Petri网的装备维修保障建模与分析

通过将任意分布随机Petri网的基本理论和算法应用到装备维修保障的建模与分析,建立了维修保障系统的任意随机Petri网模型,实现了随机Petri网中变换概率服从指数分布的限制.根据实际系统中相关数据的统计分析和经验估计,以便为利用矩姆函数分析方法对维修保障系统的性能进行分析,为维修保障决策层提供参考,获得了一些有价值的性能指标信息.     

自行火炮扭力轴载荷谱的测量及疲劳寿命预测

为预测自行火炮扭力轴寿命,对某型自行火炮在不同工况下进行实车试验,获得了多工况下扭力轴的载荷谱。受力分析表明,表面最大拉应力是扭力轴的破坏应力;提出基于随机响应面对扭力轴寿命进行预测的方法,将低周疲劳寿命表达式中的随机参数表示为标准随机变量,引人随机响应的Hermite多项展开式进行拟合,建立了扭力轴疲劳寿命的显式函数。通过对实测载荷谱进行统计分析,依据寿命表达式可以预测扭力轴疲劳寿命,并给出概率分布。该方法弥补了传统响应面法以一般多项式拟合时不能保证收敛性的缺陷。     

某型导弹故障模式自动识别系统研究

针对某型步兵战车导弹制导控制系统的维修问题,在研究了诊断对象故障特点和故障机理的基础上,运用单片机技术,电子测量技术,智能故障诊断技术,频率因子、相位因子和幅度因子相结合的分析技术以及运用在线测试和动态比较法实现了故障模式的自动判断与识别,研制了自动、快速、实时和在线检测与故障诊断设备,并详细地给出了系统故障诊断的具体实现过程。     

超混沌系统的脉冲控制与同步及其在安全通信中的应用

利用脉冲微分系统的比较系统及其稳定性定理,研究了四阶Rssler超混沌系统的脉冲控制,给出了系统渐进稳定的充分条件。通过研究2个四阶Rssler超混沌系统的脉冲同步,给出了误差系统渐进稳定的充分条件,数值模拟验证了所给结论的正确性。根据脉冲混沌安全通信系统的原理,结合笔者提出的脉冲同步律,对某一正弦信号进行了保密传输,计算机模拟结果表明了保密传输的有效性。     

主动防护网中钢丝绳网抗顶破力计算方法研究

主动防护网以其轻便美观等优点而被越来越多地应用于边坡落石防护,现阶段针对某一具体的边坡防护工程,其防护体系的设计多根据设计者的经验确定。主动防护网主要分为起围护作用的防护网和起加固作用的防护网,针对起加固作用的防护网进行了研究。根据防护网的实际工作状况,提出了防护网抗顶破力计算模型,理论分析了单根网格绳对球体落石的作用及主动防护网中钢丝绳网对球体落石的作用,推导了单根网格绳及主动防护网中钢丝绳网抗顶破力的计算公式,为起加固作用的防护网设计提供一定的参考价值。