基于随机集理论的多目标跟踪方法

多目标跟踪问题通常包括目标信号的检测与目标状态的估计,同时还涉及到对探测范围内目标数量的确定。传统的跟踪方法将目标检测、状态估计与数量确定分别使用独立的模块或算法来处理。在这种模式下,每个模块仅考虑测量数据中与其功能直接相关的信息,模块之间没有信息的交互,因而很难得到全局最优的解。基于随机集理论的多目标跟踪方法将场景内的全部目标看作一个全局变量,目标状态与目标测量分别构成各自的随机有限集。从而多目标跟踪问题可以放在一个随机集模型下的贝叶斯滤波框架中研究。在每一个滤波周期内,通过对随机集的处理,实时地估计目标的数量、状态与类型,实现多目标的联合检测、跟踪与识别。     

运载火箭随机振动环境试验条件的变带宽设计方法

针对运载火箭随机振动环境试验条件提出了基于能量等效思想的变带宽设计方法,通过采用分数倍频程数据处理方法,并确保各个频带内的均方根值与原随机振动环境的均方根值相同,有效解决传统的等带宽随机振动环境试验条件总均方根过高的问题。为了验证所提方法的有效性,通过典型管路产品进行了随机振动响应计算。结果表明,该方法既能够有效地对产品进行考核,又不至于对产品造成过考核。所提变带宽设计方法可为运载火箭随机振动环境条件的合理设计与分析提供有效手段。     

The (s,Q) inventory model with Erlang lead time and deterministic demand

We develop a simple, approximately optimal solution to a model with Erlang lead time and deterministic demand. The method is robust to misspecification of the lead time and has good accuracy. We compare our approximate solution to the optimal for the case where we have prior information on the lead‐time distribution, and another where we have no information, except for computer‐generated sample data. It turns out that our solution is as easy as the EOQ's, with an accuracy rate of 99.41% when prior information on the lead‐time distribution is available and 97.54–99.09% when only computer‐generated sample information is available. Apart from supplying the inventory practitioner with an easy heuristic, we gain insights into the efficacy of stochastic lead time models and how these could be used to find the cost and a near‐optimal policy for the general model, where both demand rate and lead time are stochastic. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Newsvendor problems with sequentially revealed demand information

This article analyzes a capacity/inventory planning problem with a one‐time uncertain demand. There is a long procurement leadtime, but as some partial demand information is revealed, the firm is allowed to cancel some of the original capacity reservation at a certain fee or sell off some inventory at a lower price. The problem can be viewed as a generalization of the classic newsvendor problem and can be found in many applications. One key observation of the analysis is that the dynamic programming formulation of the problem is closely related to a recursion that arises in the study of a far more complex system, a series inventory system with stochastic demand over an infinite horizon. Using this equivalence, we characterize the optimal policy and assess the value of the additional demand information. We also extend the analysis to a richer model of information. Here, demand is driven by an underlying Markov process, representing economic conditions, weather, market competition, and other environmental factors. Interestingly, under this more general model, the connection to the series inventory system is different. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 2012     

Averaging frameworks for simulation optimization with applications to simulated annealing

We present two frameworks for designing random search methods for discrete simulation optimization. One of our frameworks is very broad (in that it includes many random search methods), whereas the other one considers a special class of random search methods called point‐based methods, that move iteratively between points within the feasible region. Our frameworks involve averaging, in that all decisions that require estimates of the objective function values at various feasible solutions are based on the averages of all observations collected at these solutions so far. Also, the methods are adaptive in that they can use information gathered in previous iterations to decide how simulation effort is expended in the current iteration. We show that the methods within our frameworks are almost surely globally convergent under mild conditions. Thus, the generality of our frameworks and associated convergence guarantees makes the frameworks useful to algorithm developers wishing to design efficient and rigorous procedures for simulation optimization. We also present two variants of the simulated annealing (SA) algorithm and provide their convergence analysis as example application of our point‐based framework. Finally, we provide numerical results that demonstrate the empirical effectiveness of averaging and adaptivity in the context of SA. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Optimal inventory control policy for periodic‐review inventory systems with inventory‐level‐dependent demand

We consider a setting in which inventory plays both promotional and service roles; that is, higher inventories not only improve service levels but also stimulate demand by serving as a promotional tool (e.g., as the result of advertising effect by the enhanced product visibility). Specifically, we study the periodic‐review inventory systems in which the demand in each period is uncertain but increases with the inventory level. We investigate the multiperiod model with normal and expediting orders in each period, that is, any shortage will be met through emergency replenishment. Such a model takes the lost sales model as a special case. For the cases without and with fixed order costs, the optimal inventory replenishment policy is shown to be of the base‐stock type and of the (s,S) type, respectively. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

混沌随机频率步进信号分析与处理

混沌具有类随机性、对初值敏感、易于产生和控制,频率步进信号易于工程实现和处理,结合二者的优势,提出一种基于混沌序列的随机频率步进雷达信号。介绍了信号产生模型,从理论上推导、分析了该信号的模糊函数和互相关函数性能,给出了信号直接相关和先排序存储、后匹配滤波两种回波处理方法。应用四种典型混沌进行数值仿真,并和已有的线性频率步进信号、高斯和均匀随机频率步进信号进行对比分析。结果表明,混沌随机频率步进信号具有较优良的性能,是一种有潜力的雷达信号。     

基于作战任务的多机种故障备件需求模型

通过分析战时故障备件的需求特点,对备件的工作时间进行讨论,改进了传统的单机故障备件需求模型。根据多机种协同作战任务的不同,引入备件工作运行比的概念,在考虑飞机是否战损的前提下,建立了基于作战任务的多机种故障备件需求模型。算例分析证明了模型的有效性。