A two‐echelon inventory‐location problem with service considerations

We study the problem of designing a two‐echelon spare parts inventory system consisting of a central plant and a number of service centers each serving a set of customers with stochastic demand. Processing and storage capacities at both levels of facilities are limited. The manufacturing process is modeled as a queuing system at the plant. The goal is to optimize the base‐stock levels at both echelons, the location of service centers, and the allocation of customers to centers simultaneously, subject to service constraints. A mixed integer nonlinear programming model (MINLP) is formulated to minimize the total expected cost of the system. The problem is NP‐hard and a Lagrangian heuristic is proposed. We present computational results and discuss the trade‐off between cost and service. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

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     

C~4ISR系统任务实时性的评价方法

提出一种定量评价C4ISR(Command Control Communication Computer Intelligence Surveillance and Reconnaissance)系统任务实时性方法--时序着色模糊时间Petri网(TCFTPN)方法.用时序逻辑公式来限制着色Petri网的变迁引发行为,用模糊时间来表示各工作过程的时延特性和降级工作问题.通过估计在规定的时间内标识从任务开始状态到达任务完成状态的概率来确定C4ISR系统的任务实时性.     

战术数据链网络设计优化方法

网络设计优化问题直接关系到战术数据链系统效能的发挥。在分析数据链系统中不同消息类别有不同系统响应时间要求的基础上,提出了一种新的网络设计优化方法。通过建立模型讨论了单个数据链轮询网络的轮询周期、网络成员容量、每个轮询周期内各成员的点名次数等因素间的数学关系。并以Link-11为例进行分析计算。结果表明,该分析方法有效可行,为解决战术数据链网络设计及优化问题提供了一种思路。     

大型消防装备采购模式及全寿命期费用控制问题探析

大型消防装备采购模式存在的一些问题,影响了大型消防装备全寿命期的经费使用效益,导致大型消防装备的购置费用高而效率低,装备闲置和利用率不高,装备全寿命期费用控制效果较差,必须建立大型消防装备全寿命费用管理体系,提高大型消防装备投资的效率。     

联合补充博弈的费用分摊

就一个仓库、多个零售商,对联合订货费用函数的模型进行分析,给出了一个求解最佳订货周期的多项式时间的算法,且算法的时间复杂性为O（nlogn）。利用文献[8]中的技巧,给出了该库存博弈的核。     

电磁辐射测量仪的抗干扰设计

简要介绍根据电磁辐射测量理论设计的一款电磁辐射测量仪,并在此基础上详细阐述各种抗干扰措施,包括软件和硬件相应的抗干扰设计。实验证明,该测量仪运行正常,抗干扰性能良好。     

基于动态时间规整算法的车辆目标分类研究

将动态时间规整(Dynamic Time Warping)算法应用于地面车辆目标的分类识别中。基于微多普勒效应原理,建立了轮式车辆和履带式车辆雷达回波模型,对两种车辆目标微多普勒信号的差异性进行了分析,并结合实测数据,验证了理论分析的正确性。在杂波抑制及速度归一化处理的基础上,利用动态时间规整算法,将提取出的车辆目标的累积失真距离作为目标分类识别的依据,实现了轮式车辆和履带式车辆的自动分类。基于实测数据的实验结果表明,该方法在不同信噪比条件下都具有较好的分类性能。     

一种基于蚁群算法的准动态防空武器分配算法

武器目标分配问题是一个典型的限制组合优化问题,旨在得到在整个防御阶段中针对目标函数的最优武器分配方案。分配算法主要分为静态和动态两大类。针对传统静态分配模型中存在的几点问题,提出了基于时间窗的准动态武器目标分配算法,该算法综合考虑拦截概率、拦截时间和武器耗费多个优化指标,并将该算法推广至多类防空武器的优化分配中。通过大量实验验证,该算法在性能、时间复杂度等方面均有较大优势,并且能较好地适应战场态势的变化,及时调整分配方案,具有很好的实用性。     

坦克底盘角振动对火炮射击精度影响机理研究

实车试验表明,在行进间射击试验时,当车辆超过一定车速(行进间射击车速)时,射击精度或射击命中率会发生大幅度的下降。针对这个问题,建立了坦克底盘角振动导致的射击偏差的数学模型;并结合实车试验数据,对射击延迟时间内底盘角振动造成的火炮射击偏差进行了全面分析。分析研究表明:在相同的行驶车速条件下,车辆底盘角速度、姿态角变化量随着射击延迟时间的增大而增大;在相同的射击延迟时间内,车辆底盘角速度、姿态角变化量与射角偏差随着行驶车速的增大而增大;其中射角偏差引起的目标距离偏差是弹丸横向速度导致的目标距离偏差的3倍~5倍。因此,随着行驶车速增加而增加的射角偏差增大是行进间射击车速受限的主要原因。