单星定向原理及GPS仿真试验

介绍了一种新的卫星定向方法,该方法仅利用一颗地球静止轨道卫星完成定向;介绍了利用GPS卫星进行单星定向原理验证试验的方法、条件和结果。试验结果表明,对于3m长基线,单星定向精度可达0.05°。从而说明利用一颗地球静止轨道卫星进行定向,在原理上是正确可行的。     

导弹测试系统中动态激励设备的调速控制与变频器的应用

导弹自动驾驶仪敏感部件功能状态的测试,是导弹实施综合测试内容的重要项目之一。实施敏感部件的测试的前提条件之一,是要有动态激励信号产生。产生动态激励信号的设备是动态激励装置。动态激励装置由驱动电机进行驱动。对驱动调速机构、调速原理以及变频器的应用,做出概要性阐述。     

身管武器生产定型时机的量化决策

提出以大型试验批个数来确定身管武器生产定型时机的方法,并依据统计决策与贝叶斯分析方法,结合专家信息与收集的数据,对身管武器生产定型时机作出量化判定,为定型委员会的决策提供理论与数据支持。     

适于卫星闪电监测系统的地面站数目配置初探

闪电监测载荷搭载在不同卫星平台时,地面站对它的观测时间都会发生相应的改变,文中对其进行了计算,并对不同轨道高度下所需的地面站个数作了简要分析。     

舰船航渡过程中的松弛时间与航渡策略问题

针对舰船特点和任务要求,提出了舰船航渡中的松弛时间问题。在对问题分析的基础上,给出了松弛时间的定义并对其进行了建模,讨论了航渡失败的判断准则,给出了松弛时间的上下限以及航渡中实际的松弛时间的计算方法,并采用仿真的方法进行了典型航渡过程的松弛时间和成功概率的计算。在大量计算的基础上,初步探讨了航渡成功概率与各类航渡参数之间的关系,并对舰船最优航渡策略问题进行了初步分析,最后对于优化目标、计算初值、结果的表达方式等提出了一个可行的解决方案。     

一类有增益网络的最大流模型

一般带容量限制的网络图中流出源点与流入汇点的流量相等,但在实际应用中,存在一类流量经过弧发生变化的网络,使得流出源点与流入汇点的流量不相等。针对此类问题,建立了增益网络最大流模型,并通过增设虚弧将增益网络转换成循环网络,利用循环网络中汇点流量瞬间平衡的优点简化了模型。最后,结合实例进行分析,编写程序对实例进行了计算,计算结果验证了该模型的有效性。     

一类微分方程组极限环的不存在性

在系统奇点唯一的条件下,研究了一类微分方程组不存在极限环的的充分条件,运用和发展了以往的结果。     

一类非线性脉冲时滞抛物型偏微分方程组解的振动性

讨论了一类含脉冲的时滞抛物型方程组非零解的振动性,利用了Green定理以及Jensen不等式,得出了该方程在Robin边界条件下非零解振动的若干准则。     

Irreducibility of joint inventory positions in an assemble‐to‐order system under (r,nQ) policies

In a typical assemble‐to‐order system, a customer order may request multiple items, and the order may not be filled if any of the requested items are out of stock. A key customer service measure when unfilled orders are backordered is the order‐based backorder level. To evaluate this crucial performance measure, a fundamental question is whether the stationary joint inventory positions follow an independent and uniform distribution. In this context, this is equivalent to the irreducibility of the Markov chain formed by the joint inventory positions. This article presents a necessary and sufficient condition for the irreducibility of such a Markov chain through a set of simultaneous Diophantine equations. This result also leads to sufficient conditions that are more general than those in the published reports. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Averaging frameworks for simulation optimization with applications to simulated annealing

We present two frameworks for designing random search methods for discrete simulation optimization. One of our frameworks is very broad (in that it includes many random search methods), whereas the other one considers a special class of random search methods called point‐based methods, that move iteratively between points within the feasible region. Our frameworks involve averaging, in that all decisions that require estimates of the objective function values at various feasible solutions are based on the averages of all observations collected at these solutions so far. Also, the methods are adaptive in that they can use information gathered in previous iterations to decide how simulation effort is expended in the current iteration. We show that the methods within our frameworks are almost surely globally convergent under mild conditions. Thus, the generality of our frameworks and associated convergence guarantees makes the frameworks useful to algorithm developers wishing to design efficient and rigorous procedures for simulation optimization. We also present two variants of the simulated annealing (SA) algorithm and provide their convergence analysis as example application of our point‐based framework. Finally, we provide numerical results that demonstrate the empirical effectiveness of averaging and adaptivity in the context of SA. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012