Assessing the value of demand sharing in supply chains

We consider the problem of assessing the value of demand sharing in a multistage supply chain in which the retailer observes stationary autoregressive moving average demand with Gaussian white noise (shocks). Similar to previous research, we assume each supply chain player constructs its best linear forecast of the leadtime demand and uses it to determine the order quantity via a periodic review myopic order‐up‐to policy. We demonstrate how a typical supply chain player can determine the extent of its available information in the presence of demand sharing by studying the properties of the moving average polynomials of adjacent supply chain players. The retailer's demand is driven by the random shocks appearing in the autoregressive moving average representation for its demand. Under the assumptions we will make in this article, to the retailer, knowing the shock information is equivalent to knowing the demand process (assuming that the model parameters are also known). Thus (in the event of sharing) the retailer's demand sequence and shock sequence would contain the same information to the retailer's supplier. We will show that, once we consider the dynamics of demand propagation further up the chain, it may be that a player's demand and shock sequences will contain different levels of information for an upstream player. Hence, we study how a player can determine its available information under demand sharing, and use this information to forecast leadtime demand. We characterize the value of demand sharing for a typical supply chain player. Furthermore, we show conditions under which (i) it is equivalent to no sharing, (ii) it is equivalent to full information shock sharing, and (iii) it is intermediate in value to the two previously described arrangements. Although it follows from existing literature that demand sharing is equivalent to full information shock sharing between a retailer and supplier, we demonstrate and characterize when this result does not generalize to upstream supply chain players. We then show that demand propagates through a supply chain where any player may share nothing, its demand, or its full information shocks (FIS) with an adjacent upstream player as quasi‐ARMA in—quasi‐ARMA out. We also provide a convenient form for the propagation of demand in a supply chain that will lend itself to future research applications. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 515–531, 2014     

威布尔分布的战术导弹可靠性试验信息融合方法

针对战术导弹可靠性试验小子样问题,提出了基于威布尔分布,利用小概率原理,针对不同试验环境下试验数据的融合方法。该方法扩大了战术导弹可靠性试验的统计子样,提高了可靠性评定的可信度。     

求解卷积公式的一种新方法

基于数形结合方法以及变量代换方法发现计算卷积公式存在某些不足之处,研究卷积公式的计算方法,给出一种新的确定积分限的方法.该方法直观明了、容易理解和掌握并且可操作性强,有效避免作图和分析图形的繁琐,并举例说明了该应用方法.     

Inequality‐based reliability estimates for complex systems

Full‐system testing for large‐scale systems is often infeasible or very costly. Thus, when estimating system reliability, it is desirable to use a method that uses subsystem tests, which are often less expensive and more feasible. This article presents a method for bounding full‐system reliabilities based on subsystem tests and, if available, full‐system tests. The method does not require that subsystems be independent. It accounts for dependencies through the use of certain probability inequalities. The inequalities provide the basis for valid reliability calculations while not requiring independent subsystems or full‐system tests. The inequalities allow for test information on pairwise subsystem failure modes to be incorporated, thereby improving the bound on system reliability. We illustrate some of the properties of the estimates via an example application. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

箔条干扰条件下舰空导弹单发杀伤概率计算

目前,对导弹抗干扰能力的要求越来越高,干扰条件下的导弹单发命中概率已成为评定导弹性能的重要指标.针对箔条干扰条件下舰空导弹单发杀伤概率评定,建立了雷达导引头接收端信干比模型、舰空导弹圆目标落入概率模型以及抗干扰改善因子模型,从而构建了箔条干扰条件下舰空导弹单发命中概率模型,计算出真实有效的单发命中概率.     

基于EKF算法的弹道导弹助推段跟踪建模与仿真

围绕弹道导弹助推段跟踪问题,分析了助推段反弹道导弹的基本作战过程,建立了弹道导弹助推段动力学模型,分别就单传感器/单弹道导弹和多传感器/多弹道导弹两种情况建立了基于EKF算法的弹道导弹助推段跟踪模型,并通过算例验证了模型和算法的有效性,可为助推段反弹道导弹建模与仿真提供一定的参考。     

智能水雷主动干扰方法研究

针对传统的扫雷方法在清除智能化水雷引信方面存在的不足,分析了利用主动干扰信号反水雷的思路,通过分析智能引信的工作机理及在干扰背景下对目标信号的检测能力,建立了基于奈曼-皮尔逊准则的主动干扰反水雷模型.针对水雷磁引信,选择电极式电磁扫雷具为干扰源,以中型舰船为保护对象,通过计算三者的相互位置与信噪比的关系,以及水雷检测出...     

非平稳高斯序列最大值的几乎处处中心极限定理

在较弱的条件下,研究了一类非平稳高斯序列的几乎处处中心极限定理.设{Xa,n≥1}为一非平稳高斯序列,记其协方差为rij=Cov(Xi,Xj).假设该序列满足如下条件:对充分大的n,若存在0<α<1当|i-j|>nα时,rijlog|j-i|(l0glog|j-i|)1+ε一致有界.在这一条件下,通过利用概率极限理论,...     

基于观测值和真值计算的概率差异分析

作战效能与攻击决策通常都用概率描述一些不确定问题,然而概率有主观与客观之分,为了说明其不同,以一个假想的直进射击问题为例,只考虑目标运动速率误差,对已知真值或观测值所面对的不确定问题的实质进行了讨论。结论表明,当涉及射击成功概率这些问题时,对其实质与作用有必要给出清楚的说明。只知观测值所计算的概率是主观的,可用于决策信念的支持,基于主观概率进行决策,其精确性十分依赖于所使用的关于观测量真值先验知识的精确性。     

进度风险的随机网络建模与仿真分析

为研究装备研制工程进度的风险分布特征,建立了包含正态分布、β分布、三角分布的随机网络进度风险分析模型,通过蒙特卡罗法仿真获得工程项目的进度估计及其统计分布特性,从而获得工程总工期的风险,并结合实例进行了分析.