有源、无源联合探测系统综合性能分析

根据无源探测系统与有源雷达组成的联合探测系统,给出了一种有源、无源联合探测系统的探测模型,定性、定量的仿真分析了不同布站方法时,系统的探测精度、探测模糊区分布问题,得出了联合探测系统的最优布站方法;与无源探测系统相比较,联合探测系统提高了系统探测精度,改善了探测模糊区.仿真结果可为工程实践中雷达组网的优化部署提供理论依据.     

舰炮武器系统动态误差检测方法

舰炮武器系统动态误差是系统动态性能的重要指标,精确测量舰炮武器系统动态误差一直是比较困难的问题,提出一种比较先进的动态误差测量方法,可以按给定间隔时间连续测量和录取舰炮不稳定方向瞄准角和高低瞄准角动态误差,监测系统的动态过程.对舰炮武器系统动态检测和调试,提高系统射击精度有较大的现实意义.     

履带车辆动力性仿真研究

为仿真履带车辆动力性,建立了动力性评价指标的仿真模型,并以某型车为实例,应用Matlab语言编程计算得出理论值,通过与试验值比较验证了模型的有效性和准确性。     

考虑落角约束与驾驶仪特性的自适应RBF空间末制导律

为使大口径舰炮制导炮弹在打击近岸机动目标的末制导段满足落角约束,现考虑自动驾驶仪动态特性,基于自适应RBF逼近网络与动态面滑模提出一种空间末制导律。构建空间弹目相对运动模型,通过带改进微分跟踪器的扩张状态观测器估计目标加速度。为零化视线角跟踪误差与视线角速率,采用自适应指数趋近律设计非奇异终端滑模动态面,并运用自适应RBF逼近网络削弱控制指令抖振。通过Lyapunov第二法证明了全系统中视线角跟踪误差与视线角速率均最终一致有界。仿真实验表明：该末制导律使制导炮弹在空间中打击具有不同机动形式的近岸目标时,均具备良好的末制导性能。     

Balancing a one‐way corridor capacity and safety‐oriented reliability: A stochastic optimization approach for metro train timetabling

In urban rail transit systems of large cities, the headway and following distance of successive trains have been compressed as much as possible to enhance the corridor capacity to satisfy extremely high passenger demand during peak hours. To prevent train collisions and ensure the safety of trains, a safe following distance of trains must be maintained. However, this requirement is subject to a series of complex factors, such as the uncertain train braking performance, train communication delay, and driver reaction time. In this paper, we propose a unified mathematical framework to analyze the safety‐oriented reliability of metro train timetables with different corridor capacities, that is, the train traffic density, and determine the most reliable train timetable for metro lines in an uncertain environment. By employing a space‐time network representation in the formulations, the reliability‐based train timetabling problem is formulated as a nonlinear stochastic programming model, in which we use 0‐1 variables to denote the time‐dependent velocity and position of all involved trains. Several reformulation techniques are developed to obtain an equivalent mixed integer programming model with quadratic constraints (MIQCP) that can be solved to optimality by some commercial solvers. To improve the computational efficiency of the MIQCP model, we develop a dual decomposition solution framework that decomposes the primal problem into several sets of subproblems by dualizing the coupling constraints across different samples. An exact dynamic programming combined with search space reduction strategies is also developed to solve the exact optimal solutions of these subproblems. Two sets of numerical experiments, which involve a relatively small‐scale case and a real‐world instance based on the operation data of the Beijing subway Changping Line are implemented to verify the effectiveness of the proposed approaches.     

Doubly Stochastic Sequential Assignment Problem

This article introduces the Doubly Stochastic Sequential Assignment Problem (DSSAP), an extension of the Sequential Stochastic Assignment Problem (SSAP), where sequentially arriving tasks are assigned to workers with random success rates. A given number of tasks arrive sequentially, each with a random value coming from a known distribution. On a task arrival, it must be assigned to one of the available workers, each with a random success rate coming from a known distribution. Optimal assignment policies are proposed for DSSAP under various assumptions on the random success rates. The optimal assignment algorithm for the general case of DSSAP, where workers have distinct success rate distribution, has an exponential running time. An approximation algorithm that achieves a fraction of the maximum total expected reward in a polynomial time is proposed. The results are illustrated by several numerical experiments. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 124–137, 2016     

Optimal staffing in nonstationary service centers with constraints

This paper considers optimal staffing in service centers. We construct models for profit and cost centers using dynamic rate queues. To allow for practical optimal controls, we approximate the queueing process using a Gaussian random variable with equal mean and variance. We then appeal to the Pontryagin's maximum principle to derive a closed form square root staffing (SRS) rule for optimal staffing. Unlike most traditional SRS formulas, the main parameter in our formula is not the probability of delay but rather a cost‐to‐benefit ratio that depends on the shadow price. We show that the delay experienced by customers can be interpreted in terms of this ratio. Throughout the article, we provide theoretical support of our analysis and conduct extensive numerical experiments to reinforce our findings. To this end, various scenarios are considered to evaluate the change in the staffing levels as the cost‐to‐benefit ratio changes. We also assess the change in the service grade and the effects of a service‐level agreement constraint. Our analysis indicates that the variation in the ratio of customer abandonment over service rate particularly influences staffing levels and can lead to drastically different policies between profit and cost service centers. Our main contribution is the introduction of new analysis and managerial insights into the nonstationary optimal staffing of service centers, especially when the objective is to maximize profitability. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 615–630, 2017     

Capacity expansion and cost efficiency improvement in the warehouse problem

The warehouse problem with deterministic production cost, selling prices, and demand was introduced in the 1950s and there is a renewed interest recently due to its applications in energy storage and arbitrage. In this paper, we consider two extensions of the warehouse problem and develop efficient computational algorithms for finding their optimal solutions. First, we consider a model where the firm can invest in capacity expansion projects for the warehouse while simultaneously making production and sales decisions in each period. We show that this problem can be solved with a computational complexity that is linear in the product of the length of the planning horizon and the number of capacity expansion projects. We then consider a problem in which the firm can invest to improve production cost efficiency while simultaneously making production and sales decisions in each period. The resulting optimization problem is non‐convex with integer decision variables. We show that, under some mild conditions on the cost data, the problem can be solved in linear computational time. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 367–373, 2016     

高动态GNSS信号多普勒模拟任意阶DDS合成器设计*

为高精度模拟高动态条件下GNSS信号的多普勒特性,本文提出一种任意阶DDS信号合成器的设计方法。设计了任意阶DDS信号合成器的结构;通过理论分析,推导了各级累加器相位初值的计算公式;给出了字长选择方法;经仿真与验证,该方法能精确模拟GNSS信号的多普勒特性。此外,本文提出的DDS设计方法不受阶数的限制,可普遍应用于各类信号模拟器的设计。     

电磁轨道发射器动态发射过程的数值模拟

针对电磁轨道发射器动态发射过程的数值模拟问题,基于矢量磁位A和时间积分标量电位V,采用节点单元法,并选择运动坐标系描述运动问题,推导出动态发射下的电磁轨道发射器三维涡流场有限元离散方程。结合温度场控制方程,建立电磁轨道发射器的三维电磁-温度耦合有限元模型。针对一个电磁轨道发射器动态发射问题,对模型进行数值模拟,得到了动态发射下轨道及电枢的温度场分布特点及发射器电感梯度随时间的变化规律。计算结果表明,模型计算出的脉冲电流峰值、出口电流大小、出口速度等参数均与试验结果吻合较好,验证了所开发的有限元程序代码的正确性。