Coordination of pricing and inventory control across products

We consider the joint pricing and inventory‐control problem for a retailer who orders, stocks, and sells two products. Cross‐price effects exist between the two products, which means that the demand of each product depends on the prices of both products. We derive the optimal pricing and inventory‐control policy and show that this policy differs from the base‐stock list‐price policy, which is optimal for the one‐product problem. We find that the retailer can significantly improve profits by managing the two products jointly as opposed to independently, especially when the cross‐price demand elasticity is high. We also find that the retailer can considerably improve profits by using dynamic pricing as opposed to static pricing, especially when the demand is nonstationary. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

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.     

火控系统动态精度环绕测试设计方法

借鉴环绕BIT技术的思想,提出一种火控系统动态精度环绕测试的设计方法.该方法充分利用火控计算机的固有资源,通过增加少量接口转换电路(一组现在点坐标输出接口和一组射击诸元输入接口),来提高火控系统动态精度检查测试性水平.对于采用环绕测试设计的火控系统,只需使用两根外接电缆,无须外接检测计算机,即可完成动态精度检查的任务,从而显著降低了操作复杂性.该设计方法的一个优点是不会影响系统的可靠性.     

多操纵面战斗机动态控制分配策略研究(英文)

现代先进飞机配置多个操纵面且又冗余,这有利于实现非常规飞行,提高飞机敏捷性,使飞机在机动和故障时有更多的选择,但是同时也导致了飞机控制设计复杂度的增加.为了达到更好的效果,就必须利用控制分配器来充分利用多操纵面的不同带宽.从频率域角度出发,研究了动态控制分配方法,并将其应用于某型先进战斗机的控制分配器设计中,利用鸭翼的频率特性抵消府舱过载,经仿真验证,采用动态控制分配策略时,可以有效地减小座舱过载,同时还可以减小配平阻力,取得了良好的控制效果.     

带有模糊干扰观测器的高超声速飞行器一体化制导控制方法

为充分利用高超声速飞行器在俯冲段的质心运动与绕质心运动之间的耦合作用和飞行过程中的不确定性,基于模糊干扰观测器提出三维一体化制导与控制问题。根据飞行器的动力学方程以及飞行器-目标的视线角相对运动方程,推导出适用于倾斜转弯控制的一体化制导控制模型。针对模型中的不确定性采用模糊干扰观测器进行补偿,并使用块动态面方法设计一种一体化制导控制律。通过选取适当的李雅普诺夫函数证明闭环系统状态的一致毕竟有界性。仿真结果验证了该一体化制导控制方法的有效性和鲁棒性。     

一种防空自动化系统效能的模糊综合评估方法

针对防空自动化系统的组成,给出了防空自动化系统效能的指标体系,并通过分析防空自动化系统静态效能和动态效能的关系,运用模糊综合评估和系统性能评价等级划分的方法,在防空自动化系统静态效能评估的基础上,研究了防空自动化系统的动态效能,提出了一种静态效能与动态效能相结合的防空自动化系统模糊综合评估方法。     

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.     

三关节机器人的神经网络补偿自适应控制器设计

三关节机器人广泛用于工业生产、轮式或履带式排爆机器人,为了补偿由于机器人结构参数、作业环境干扰等不确定性因素造成的机器人动力学模型的不确定性,将机器人动力学模型分解为名义模型和误差模型两部分,其误差模型采用RBF神经网络进行补偿,得到其估计信息,神经网络的输出权值根据Lyapunov稳定性理论采用自适应算法进行调整。所设计的神经网络补偿自适应控制器解决了不确定性机器人动力学系统控制器设计的不确定性问题,同时,通过定义Lyapunov函数,证明了控制器能渐近、稳定地跟踪期望轨迹。机器人的3个关节在控制器的作用下,约在5 s时达到期望轨迹,神经网络约在5 s时逼近机器人动力学模型的误差模型,实验结果表明了机器人关节对期望轨迹具有良好的轨迹跟踪性能。     

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。     

虚拟环境下某型迫击炮自动机故障预测仿真分析研究

在对某迫击炮自动机的结构组成和机构动作分析的基础上,应用ADAMS软件建立了该武器自动机的虚拟样机模型,并结合实验数据和理论数据对自动机连发射击仿真结果的对比,验证了虚拟样机的正确性。以虚拟样机为工具,对自动机常见故障的影响因素进行了仿真分析和计算,为该武器的故障预测提供了理论依据和数据支持。