双频去相关单历元动态解算整周模糊度研究

针对GPS实时动态精密相对定位应用背景,提出一种整周模糊度实时求解方法。采用宽巷组合载波相位双差、伪距双差观测信息建立观测模型;对浮点模糊度协方差阵进行一次Cholesky分解,构造了浮点转换矩阵,使浮点模糊度完全去相关;推导确定整周模糊度的搜索空间;利用最小残差平方和搜索准则,确定单历元整周模糊度,并用OVT检验方法,对不同历元得到的整周模糊度进行一致性检验。结果表明,观测量误差均方差取值对整周模糊度搜索空间和成功率有较大影响,附加OVT检验的双频去相关单历元动态解算整周模糊度方法正确可行。     

Concave envelopes of monomial functions over rectangles

The construction of convex and concave envelopes of real‐valued functions has been of interest in mathematical programming for over 3 decades. Much of this interest stems from the fact that convex and concave envelopes can play important roles in algorithms for solving various discrete and continuous global optimization problems. In this article, we use a simplicial subdivision tool to present and validate the formula for the concave envelope of a monomial function over a rectangle. Potential algorithmic applications of this formula are briefly indicated. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

区间分解组合迭代算法用于非确定结构系统的静力区间分析

对于结构参数向量界限绝对离差较大的非确定结构系统,迭代计算收敛条件难以满足,修正迭代算法不能直接用于其区间有限元静力控制方程的求解。采用区问分解组合求解策略,考虑区间矩阵、向量元素间的相关性,直接对结构参数区间进行区间分解,将非确定结构系统区间有限元控制方程的求解转化为若干个子区间有限元静力控制方程的修正迭代求解,提出了一种求解过程可逆的区间分解组合迭代算法,用于结构参数向量界限绝对离差较大的非确定结构系统的静力区间分析。算例结果表明,该方法是有效的。     

基于GO法的多阶段共因失效任务系统可靠性评估

为了解决部件阶段依赖性与共因失效给系统可靠性分析带来的复杂性,针对多阶段共因失效任务系统,结合GO法易于处理有时序、含共因失效系统可靠性分析的特点,首先,将前一阶段的输出信号作为后一阶段的输入信号,建模时首尾连接各阶段模型,建立整个任务系统的隐性GO模型;其次,在进行各信号流状态组合运算时,融入阶段代数处理部件的阶段依赖性;再次,用隐性共因失效分析,将共因失效对系统的影响在状态组合的定量分析中表达出来,得到所需系统可靠性指标;最后,与基于二元决策图的算法进行对比验证。结果表明:GO法可以简捷、准确地处理多阶段共因失效任务系统可靠性评估问题。     

Stein–Chen approximation and error bounds for order fill rates in assemble‐to‐order systems

Assemble‐to‐order (ATO) is an important operational strategy for manufacturing firms to achieve quick response to customer orders while keeping low finished good inventories. This strategy has been successfully used not only by manufacturers (e.g., Dell, IBM) but also by retailers (e.g., Amazon.com). The evaluation of order‐based performance is known to be an important but difficult task, and the existing literature has been mainly focused on stochastic comparison to obtain performance bounds. In this article, we develop an extremely simple Stein–Chen approximation as well as its error‐bound for order‐based fill rate for a multiproduct multicomponent ATO system with random leadtimes to replenish components. This approximation gives an expression for order‐based fill rate in terms of component‐based fill rates. The approximation has the property that the higher the component replenishment leadtime variability, the smaller the error bound. The result allows an operations manager to analyze the improvement in order‐based fill rates when the base‐stock level for any component changes. Numerical studies demonstrate that the approximation performs well, especially when the demand processes of different components are highly correlated; when the components have high base‐stock levels; or when the component replenishment leadtimes have high variability. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

教、训、战一体化教学训练方式探析

上海公安教育坚持＂实战为主导、实训为主线、实用为主旨＂的理念,强化顶层设计,实施＂四个交融＂,科学组织实施,开创了以民警岗位能力为目标,＂教、训、战＂一体的第二专科教学训练方式。     

武器-目标分配(WTA)问题研究进展

对武器-目标分配(WTA)问题的研究现状与进展进行了总结与述评.介绍了WTA问题的概念、基本模型、数学性质以及WTA问题研究的基本内容.目前WTA问题的研究内容主要集中在模型研究与算法研究两个方面.模型研究以静态模型的研究为主,但动态模型的研究还不够深入;算法研究则主要采用智能算法对WTA问题进行求解.目前基本上已经解决了小规模的静态WTA问题,但尚未有效解决大规模的动态WTA问题.     

线型数据通道高层综合的运算单元优化分配算法

运算单元分配是高层综合的关键算法之一。采用了一种面向数字信号处理应用、规则的线型数据通道模型,其中心思想是全局互联的最小化。以最小着色算法构造的一个初始分配为起点,采用随机进化算法对其进行迭代改善,以减小数据寄存器数和运算单元之间的数据交换。最后还给出了典型实例的实验结果。     

Non‐zero‐sum nonlinear network path interdiction with an application to inspection in terror networks

A simultaneous non‐zero‐sum game is modeled to extend the classical network interdiction problem. In this model, an interdictor (e.g., an enforcement agent) decides how much of an inspection resource to spend along each arc in the network to capture a smuggler. The smuggler (randomly) selects a commodity to smuggle—a source and destination pair of nodes, and also a corresponding path for traveling between the given pair of nodes. This model is motivated by a terrorist organization that can mobilize its human, financial, or weapon resources to carry out an attack at one of several potential target destinations. The probability of evading each of the network arcs nonlinearly decreases in the amount of resource that the interdictor spends on its inspection. We show that under reasonable assumptions with respect to the evasion probability functions, (approximate) Nash equilibria of this game can be determined in polynomial time; depending on whether the evasion functions are exponential or general logarithmically‐convex functions, exact Nash equilibria or approximate Nash equilibria, respectively, are computed. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 139–153, 2017     

油料消耗神经网络组合预测模型

油料消耗单一预测模型精度不高,难以适应信息化条件下精确保障需要。以单一的神经网络预测模型、时间序列预测模型和灰色预测模型为组合预测的基础,利用神经网络求取3种预测模型的组合预测权重系数,将这3种单一预测模型的预测结果作为神经网络组合预测模型的输入,求得一个新的预测结果。平均相对误差和均方差比表明,神经网络组合预测模型比单一预测模型更为优越。