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。     

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。     

Network design for time‐constrained delivery

To meet customer demand, delivery companies are offering an increasing number of time‐definite services. In this article, we examine the strategic design of delivery networks which can efficiently provide these services. Because of the high cost of direct connections, we focus on tree‐structured networks. As it may not be possible to identify a tree‐structured network that satisfies all of the delivery guarantees, we allow these guarantees to be violated but seek to minimize the sum of the violations. We establish the complexity of the problem and exploit an empirically identified solution structure to create new neighborhoods which improve solution values over more general neighborhood structures. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Scheduling parallel machines with inclusive processing set restrictions

We consider the problem of assigning a set of jobs to different parallel machines of the same processing speed, where each job is compatible to only a subset of those machines. The machines can be linearly ordered such that a higher‐indexed machine can process all those jobs that a lower‐indexed machine can process. The objective is to minimize the makespan of the schedule. This problem is motivated by industrial applications such as cargo handling by cranes with nonidentical weight capacities, computer processor scheduling with memory constraints, and grades of service provision by parallel servers. We develop an efficient algorithm for this problem with a worst‐case performance ratio of + ε, where ε is a positive constant which may be set arbitrarily close to zero. We also present a polynomial time approximation scheme for this problem, which answers an open question in the literature. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

In this study, we illustrate a real‐time approximate dynamic programming (RTADP) method for solving multistage capacity decision problems in a stochastic manufacturing environment, by using an exemplary three‐stage manufacturing system with recycle. The system is a moderate size queuing network, which experiences stochastic variations in demand and product yield. The dynamic capacity decision problem is formulated as a Markov decision process (MDP). The proposed RTADP method starts with a set of heuristics and learns a superior quality solution by interacting with the stochastic system via simulation. The curse‐of‐dimensionality associated with DP methods is alleviated by the adoption of several notions including “evolving set of relevant states,” for which the value function table is built and updated, “adaptive action set” for keeping track of attractive action candidates, and “nonparametric k nearest neighbor averager” for value function approximation. The performance of the learned solution is evaluated against (1) an “ideal” solution derived using a mixed integer programming (MIP) formulation, which assumes full knowledge of future realized values of the stochastic variables (2) a myopic heuristic solution, and (3) a sample path based rolling horizon MIP solution. The policy learned through the RTADP method turned out to be superior to polices of 2 and 3. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

卫星差分码偏差对北斗三号双频精密单点定位的影响

为探讨北斗三号系统不同频点组合卫星差分码偏差(differential code bias, DCB)对精密单点定位(precise point positioning, PPP)的影响,推导北斗三号系统不同频点无电离层组合卫星端DCB改正模型,并基于MGEX跟踪站连续7天4站的观测数据按7种不同双频组合进行DCB改正实验。结果表明,DCB改正对PPP精度在最初的历元有明显提升,有助于滤波的收敛及提高单天解的均方根,但对于最终定位精度无明显提升。B2a/B3I及B2b/B3I组合定位精度及收敛速度明显低于其他组合,DCB改正后有所提升。其他5种组合改正后定位精度及收敛时间相当：静态PPP单天解均方根在E、N和U方向约为5.50 cm、2.50 cm和6.25 cm,较未改正前提升20%～65%;平均收敛时间为38 min,提升约6%;动态PPP平均收敛时间为59 min,提升约20%;最终定位精度水平方向优于5 cm,高程方向优于7 cm。