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。     

多脉冲导弹可达域优化方法设计与分析

为了更合理地制定导弹的战术指标和作战任务规划,对多脉冲导弹可达域进行研究。通过引入加权的纵程和横程的组合性能指标函数,将可达域的优化问题转化为最优控制问题,建立以飞行攻角和侧滑角为双优化设计变量的多阶段多约束优化模型,采用hp自适应伪谱法对其进行求解,并着重分析多脉冲导弹发动机参数和终端约束条件对导弹可达域的影响。仿真结果表明,hp自适应伪谱法能有效解决多阶段多约束的多脉冲导弹可达域优化问题,且多脉冲导弹脉冲发动机时间间隔越小,推力比越大,装药比越小,导弹的可达域越大,相比于终端速度对可达域的影响,终端弹道倾角对可达区域的影响较小。     

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     

导航卫星广播星历参数拟合算法研究

基于GPS广播星历参数,研究了导航卫星广播星历参数的非线性最小二乘拟合算法,并推导了相应的计算公式.针对静止轨道卫星轨道倾角近似为0,致使卫星轨道的升交点定义模糊,在数据拟合过程中会导致法矩阵(HTH)奇异的问题,提出对卫星轨道进行轨道倾角变换拟合广播星历参数的方法,并获得较高的拟合精度.最后利用实际算例验证了所推公式和算法的合理性.     

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