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     

用于电压岛式功耗管理的无运放结构高精度电流采样电路

电压岛式的功耗管理在大规模SoC芯片中的应用越来越广泛,由于负载电流是反映功耗最直接的物理量,因此对负载电流的实时、精确采样是对功耗进行精确管理和控制的基础,而低压大电流又是当前大规模芯片的基本特征.在分析了几种常用的电流采样技术的基础之上,提出了一种基于电流镜采样的高精度的电流采样方案,适合于低电源电压供电,并且不需要使用运算放大器,结构简单.基于0.18μm CMOS工艺实现了该电流采样电路,各种条件下的版图模拟结果表明,对于60～1300mA的负载,该电路的采样精度最高可达99.1%,并且自身功耗不超过4mW.利用该电流采样电路,可以对负载电流进行实时有效的高精度侦测,用以作为功耗管理的依据.     

基于预计和评估结果融合的电子装备可靠性预测方法

分析了目前获得电子装备可靠性水平的可靠性预计和评估两种方法各自的优缺点,确立了融合两种方法所得结果以解决各自方法不足的思想.基于证据决策理论,以电子装备累积故障概率作为目标集,将可靠性预计结果和评估结果分别作为两批证据对目标集进行支持.利用信息融合方法,对两个利用不同源信息得出的预计结果和评估结果进行了融合,并得到了准确、实用的可靠性预测结果.最后以某型雷达为例进行实例分析,验证此方法的可行性.     

基于MSOA神经网络模型的装备保障费用预测

引入基于多步骤优化方法(MSOA)神经网络模型用以预测装备保障费用。实验结果表明,与传统的ARIMA时间序列模型和常规BP神经网络模型相比,基于MSOA神经网络预测模型具有更高预测精度。因此,该模型是一种更有效的装备保障费用预测模型。     

信道带宽对CCRW算法码跟踪精度的影响分析

码相关参考波形(CCRW)技术能够适应复杂的电磁环境和实现优异的多径抑制性能,是目前卫星导航多径抑制研究的热点。相关文献对CCRW算法码跟踪精度的研究,主要是针对无限信道带宽条件下,仿真分析闸宽参数对码跟踪精度的影响,并未分析信道带宽影响。论文推导了CCRW算法码跟踪精度表达式,分析了信道带宽对CCRW算法跟踪精度的影响并进行了仿真验证。结论表明,在无限带宽下,减小闸波宽度可提高码跟踪精度,但是在带限条件下,闸波宽度存在最优值。该结论可用于指导卫星导航接收机的CCRW算法设计。     

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。     

Expansion planning for waste‐to‐energy systems using waste forecast prediction sets

We consider an expansion planning problem for Waste‐to‐Energy (WtE) systems facing uncertainty in future waste supplies. The WtE expansion plans are regarded as strategic, long term decisions, while the waste distribution and treatment are medium to short term operational decisions which can adapt to the actual waste collected. We propose a prediction set uncertainty model which integrates a set of waste generation forecasts and is constructed based on user‐specified levels of forecasting errors. Next, we use the prediction sets for WtE expansion scenario analysis. More specifically, for a given WtE expansion plan, the guaranteed net present value (NPV) is evaluated by computing an extreme value forecast trajectory of future waste generation from the prediction set that minimizes the maximum NPV of the WtE project. This problem is essentially a multiple stage min‐max dynamic optimization problem. By exploiting the structure of the WtE problem, we show this is equivalent to a simpler min‐max optimization problem, which can be further transformed into a single mixed‐integer linear program. Furthermore, we extend the model to optimize the guaranteed NPV by searching over the set of all feasible expansion scenarios, and show that this can be solved by an exact cutting plane approach. We also propose a heuristic based on a constant proportion distribution rule for the WtE expansion optimization model, which reduces the problem into a moderate size mixed‐integer program. Finally, our computational studies demonstrate that our proposed expansion model solutions are very stable and competitive in performance compared to scenario tree approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 47–70, 2016     

基于模糊评判的某行星转向机故障预测研究

为了实现对自行火炮传动系统的预测维修,以行星转向机为例,运用动态模糊综合评判的办法,提取引起行星转向机典型故障的关键影响因素,探讨了动态模糊判断矩阵和动态权重的确定方法,在此基础上确定了其动态预测模型,并用实例验证了模型的正确性。     

任务驱动下航材需求量的GA-GM-BP预测

机务保障影响着航空装备战斗力的生成,机务保障资源是任务成功率的物质支撑.基于航材需求信息的灰色性,通过采用DEMATEL方法提取影响航空备件需求量的关键影响因素,采用遗传算法优化的灰色神经网络对需求量进行了仿真预测,其预测精度较BP神经网络和灰色神经网络都高.该方法对于其他航空机务保障资源的需求预测有借鉴意义.     

空舰导弹火控系统精度分析研究

介绍了一种空舰导弹火控系统动态精度试验的试验方法、误差分析理论和方法.用导弹火控系统的数据测量设备获取火控系统输出射击诸元参数实际值,再测量载机和靶船的位置和运动参数,经真值解算模型解算出射击诸元参数标准值.将实际值与标准值进行比较与分析,即可得知空舰导弹火控系统的动态精度是否满足要求.此方法已成功地应用于导弹火控系统精度飞行试验中.