Optimal pricing and inventory control policy in periodic‐review systems with fixed ordering cost and lost sales

This paper studies a periodic‐review pricing and inventory control problem for a retailer, which faces stochastic price‐sensitive demand, under quite general modeling assumptions. Any unsatisfied demand is lost, and any leftover inventory at the end of the finite selling horizon has a salvage value. The cost component for the retailer includes holding, shortage, and both variable and fixed ordering costs. The retailer's objective is to maximize its discounted expected profit over the selling horizon by dynamically deciding on the optimal pricing and replenishment policy for each period. We show that, under a mild assumption on the additive demand function, at the beginning of each period an (s,S) policy is optimal for replenishment, and the value of the optimal price depends on the inventory level after the replenishment decision has been done. Our numerical study also suggests that for a sufficiently long selling horizon, the optimal policy is almost stationary. Furthermore, the fixed ordering cost (K) plays a significant role in our modeling framework. Specifically, any increase in K results in lower s and higher S. On the other hand, the profit impact of dynamically changing the retail price, contrasted with a single fixed price throughout the selling horizon, also increases with K. We demonstrate that using the optimal policy values from a model with backordering of unmet demands as approximations in our model might result in significant profit penalty. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

A multilevel passenger screening problem for aviation security

Passenger prescreening is a critical component of aviation security systems. This paper introduces the Multilevel Allocation Problem (MAP), which models the screening of passengers and baggage in a multilevel aviation security system. A passenger is screened by one of several classes, each of which corresponds to a set of procedures using security screening devices, where passengers are differentiated by their perceived risk levels. Each class is defined in terms of its fixed cost (the overhead costs), its marginal cost (the additional cost to screen a passenger), and its security level. The objective of MAP is to assign each passenger to a class such that the total security is maximized subject to passenger assignments and budget constraints. This paper shows that MAP is NP‐hard and introduces a Greedy heuristic that obtains approximate solutions to MAP that use no more than two classes. Examples are constructed using data extracted from the Official Airline Guide. Analysis of the examples suggests that fewer security classes for passenger screening may be more effective and that using passenger risk information can lead to more effective security screening strategies. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

基于改进卡尔曼滤波方法的机动目标跟踪研究

针对在机动目标跟踪中当目标作高度机动飞行时卡尔曼滤波可能会出现严重发散的情况,提出利用BP神经网络校正其滤波结果,并将遗传算法应用于BP网络的训练过程,以解决BP网络训练速度慢的缺陷,提高算法的实时性。仿真表明该方法是可行的、有效的。     

基于Jerk模型的一种改进多传感器数据融合算法

简要介绍了目前存在的一些机动模型和基于状态估计的滤波算法。将Jerk模型与强跟踪滤波算法有机地结合起来,并提出了一种通过时空综合分析的测量方差自适应估计方法以优化强跟踪滤波算法中次优渐消因子和滤波增益的在线选择,同时结合多传感器数据融合具有改善滤波精度的性质,最终给出了一种基于Jerk模型的改进多传感器数据融合算法。最后,通过蒙特卡罗仿真验证了该算法的有效性。     

动态教学法在《政治学原理》课程教学中的运用

政治学原理课程在授课过程中存在着教材内容的确定性和稳定性,而无论从国际国内形势还是从政治学研究而言,政治学所关注的范围和内容又都处于动态的不断发展变化的。笔者以为,只有在授课中具体运用动态教学法,通过联系学生自身、联系社会现实、联系国家大事、联系国际政治等实际,才能使政治学原理课程在马克思主义基本原则的指导下,更富有时代特征和生活气息,使学生真正学有所获。     

聚氨酯阻尼材料的结构设计及其动态力学性能的研究

据聚合物阻尼性能定量化理论,设计合成了软段结构、分子量不同以及含支链的聚氨酯.动态力学性能测试表明,含聚环氧丙烷二醇(PPG,Mn=2 000)、聚己二酸二乙二醇(PDEA,Mn=2 000)、聚己二酸乙二醇(PEAG,Mn=2 000)软段的试样的温域宽和内耗峰高.当软段分子量增加时,材料的损耗因子增加.组份相同时,含支链比不含支链的聚氨酯试样的内耗峰高,阻尼值大.     

利用字节模式二维特征的ROP链智能检测方法

面向返回编程(return oriented programming, ROP)攻击是网络攻击者突破操作系统安全防护、实现漏洞攻击的一种主要手段,ROP链是ROP攻击的重要组成部分。为检测网络流量中的ROP链,提出了一种能自动提取ROP链特征、具有良好泛化性能的智能检测方法。该方法采用顺序抽取的方式将被测流量分成多个序列,利用滑动窗口和数值量化将输入的一维流量数据转换为二维特征向量,基于卷积神经网络模型实现对ROP链的检测。不同于已有的静态检测方法,该方法不依赖程序内存地址的上下文信息,实现简单、部署方便,且具有优异的检测性能。实验结果表明,模型最高准确率为99.4%,漏报率为0.6%,误报率为0.4%,时间开销在0.1 s以内,对真实ROP攻击流量的漏报率为0.2%。     

闪烁噪声条件下基于交互多模框架的雷达目标跟踪算法

针对传统雷达目标跟踪算法在处理闪烁噪声时面临的性能下降问题,提出一种将容积卡尔曼估计器与交互多模框架相结合的高性能滤波算法。该算法将目标状态建模为高斯分布,将闪烁噪声建模为混合高斯分布,同时将其发生概率建模为一阶马尔可夫过程;在此基础上,利用交互多模框架实现对不同高斯噪声分量的匹配滤波处理。为了减轻非线性观测条件对目标跟踪精度的影响,进一步采用容积卡尔曼估计器作为高斯近似滤波器,对目标状态进行递推预测和更新。仿真结果表明：所提算法较传统高斯混合滤波器和粒子滤波器具有更高的跟踪精度和更好的实时性能,同时还能对闪烁噪声出现时刻进行有效的估计。     

RCS特性辅助的CMIMO雷达功率资源分配方法

针对集中式多输入多输出(collocated multiple-input multiple-output, CMIMO)雷达在实际探测过程中,未有效结合目标雷达散射截面(radar cross section, RCS)高动态变化特性导致雷达跟踪精度不高甚至失跟的问题,提出一种基于目标RCS高动态特性的CMIMO雷达功率资源自适应分配方法。考虑到目标RCS特征的角度敏感性,利用目标运动状态的可预测性动态获取实际观测角度,从而完成跟踪帧的极化方式优选;在此基础上构建包含功率与RCS的多目标跟踪误差后验克拉美罗下界,将其作为目标函数进行优化,利用内点惩罚法求解该凸优化问题即可实现RCS高动态情况下的功率优化分配。实验结果表明:该方法可结合目标不同方向RCS动态分集特性实现功率的有效分配,相比于传统RCS模型分配方案,有效解决了分配方案与实际跟踪场景之间的失配问题,从而提升了CMIMO雷达的多目标跟踪性能。     

杂波环境下多目标跟踪数据关联的快速算法

数据关联是实现杂波环境下多目标跟踪的关键问题,目前公认较好的方法是联合概率数据关联（ＪＰＤＡ）,但是其计算和存储量很大,故在实际中寻求一种快速或近似的算法是十分必要的。本文提供一组有效快速算法,并在我们有关课题中得到初步验证。