军事物流配送中心作业流程建模与仿真

军事物流配送中心是军事物流的重要组成部分,加强军事物流配送中心的作业研究对于提高我军后勤保障能力有着重要的现实意义。根据军事物流配送中心的作业特点,分析了军事物流配送中心作业流程,建立了相应的作业过程仿真模型,并用Flex-sim仿真软件对军事物流配送中心作业流程进行了仿真。通过仿真结果分析,找出了作业流程中的瓶颈,为配送中心资源和流程的改进提供了依据。     

异步雷达组网协同跟踪动态传感器分配算法

针对异步雷达组网下的协同跟踪问题提出了一种基于异步顺序融合的动态传感器分配算法。该算法对异步雷达的量测值按采样时刻顺序滤波,根据滤波协方差和目标期望协方差的接近程度动态选择下一时刻跟踪的最优传感器集合。仿真分析表明该算法和基于伪量测的异步雷达组网协同跟踪传感器分配算法相比具有较少的计算量和较高的目标跟踪精度。     

基于Rényi信息增量的机动目标协同跟踪算法

针对基于多传感器组网进行机动目标跟踪的传感器管理问题,提出了一种基于Rényi信息增量的机动目标协同跟踪算法。首先结合"当前"统计模型和交互式多模型不敏卡尔曼滤波算法设计了一种变结构多模型算法,来进行机动目标的状态估计;然后以Rényi信息增量为评价准则,选择使Rényi信息增量最大的单个传感器进行目标跟踪;最后利用得到的最优加速度估计进行网格划分,更新变结构多模型中的模型集合。在一般机动及强机动场景下进行了算法性能分析,仿真结果表明,该算法能够合理地选择传感器,提高了对机动目标的跟踪精度。     

基于ModelCenter的顶置武器站稳定精度优化

顶置武器站具有系统组成类型复杂、子系统间存在耦合作用的特点,导致多学科协同仿真的优化模型难以建立。通过Adams、Simulink分别建立了顶置武器站机械系统及控制系统模型,并在多学科优化设计平台Model Center中对该机电联合仿真模型进行系统集成;在此基础上,以顶置武器站稳定精度为目标函数,采用一阶差分模型对炮控系统比例系数及积分系数进行了灵敏度分析,并采用设计探索优化器对该参数进行了优化设计。仿真结果表明,所建立的顶置武器站稳定精度多学科协同优化模型设计周期短、计算效率高,为下一步进行顶置武器站多工况、多结构参数的优化设计提供技术支撑。     

基于黑板模型的分布式协同任务决策方法研究

基于黑板模型的分布式指挥控制网络为未来复杂环境下海战中多平台间的高效协同提供了新思路,通过构建应用于多航母群联合海战的分布式协同网络,对多航母群联合海战下的系统负载进行了研究,建立了一种多平台任务决策的数学模型,采用嵌套遗传算法进行了仿真求解,得到了理想的任务决策方案。最后对由于目标函数中内部负载权重系数不同取值所引起的不同任务决策结果进行了比较,验证了将基于黑板模型的分布式协同网络应用于多航母海战协同决策的科学性,为分布式海战协同决策网络的后续研究工作奠定了基础。     

产品网络化协同开发系统信息处理模型研究

产品网络协同开发系统信息处理模型是现代制造企业从事产品开发、提高企业核心竞争力的关键。在分析产品网络化协同开发系统现状的基础上,阐明了产品网络化协同开发系统的基本内涵及实现方法。提出了基于输入、输出、知识、关系、方法和时间约束六个方面组成的产品网络化协同开发系统的信息处理统一模型;建立了一个面向产品开发全过程协同的信息流模型,构建了产品网络化协同开发平台信息流模型的软件结构,为制造企业建立产品网络协同开发平台,实现产品开发过程的信息化、科学化和规范化进行了有益的工作。     

发动机平均值模型的开发与检验

建立了一个车用增压柴油机工作过程仿真的平均值模型.这个模型重在描述发动机状态变量的时间平均值,结构紧凑,使用方便,实例计算结果与试验值符合较好,适合于电控柴油机硬件在环仿真系统应用.     

Production‐inventory systems with imperfect advance demand information and updating

We consider a supplier with finite production capacity and stochastic production times. Customers provide advance demand information (ADI) to the supplier by announcing orders ahead of their due dates. However, this information is not perfect, and customers may request an order be fulfilled prior to or later than the expected due date. Customers update the status of their orders, but the time between consecutive updates is random. We formulate the production‐control problem as a continuous‐time Markov decision process and prove there is an optimal state‐dependent base‐stock policy, where the base‐stock levels depend upon the numbers of orders at various stages of update. In addition, we derive results on the sensitivity of the state‐dependent base‐stock levels to the number of orders in each stage of update. In a numerical study, we examine the benefit of ADI, and find that it is most valuable to the supplier when the time between updates is moderate. We also consider the impact of holding and backorder costs, numbers of updates, and the fraction of customers that provide ADI. In addition, we find that while ADI is always beneficial to the supplier, this may not be the case for the customers who provide the ADI. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Scheduling economic lot sizes in deteriorating production systems

The paper considers the economic lot scheduling problem (ELSP) where production facility is assumed to deteriorate, owing to aging, with an increasing failure rate. The time to shift from an “in‐control” state to an “out‐of‐control” state is assumed to be normally distributed. The system is scheduled to be inspected at the end of each production lot. If the process is found to be in an “out‐of‐control” state, then corrective maintenance is performed to restore it to an “in‐control” state before the start of the next production run. Otherwise, preventive maintenance is carried out to enhance system reliability. The ELSP is formulated under the capacity constraint taking into account the quality related cost due to possible production of non‐conforming items, process inspection, and maintenance costs. In order to find a feasible production schedule, both the common cycle and time‐varying lot sizes approaches are utilized. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 650–661, 2003     

Dynamic learning,pricing, and ordering by a censored newsvendor

We address the problem of determining optimal ordering and pricing policies in a finite‐horizon newsvendor model with unobservable lost sales. The demand distribution is price‐dependent and involves unknown parameters. We consider both the cases of perishable and nonperishable inventory. A very general class of demand functions is studied in this paper. We derive the optimal ordering and pricing policies as unique functions of the stocking factor (which is a linear transformation of the safety factor). An important expression is obtained for the marginal expected value of information. As a consequence, we show when lost sales are unobservable, with perishable inventory the optimal stocking factor is always at least as large as the one given by the single‐period model; however, if inventory is nonperishable, this result holds only under a strong condition. This expression also helps to explain why the optimal stocking factor of a period may not increase with the length of the problem. We compare this behavior with that of a full information model. We further examine the implications of the results to the special cases when demand uncertainty is described by additive and multiplicative models. For the additive case, we show that if demand is censored, the optimal policy is to order more as well as charge higher retail prices when compared to the policies in the single‐period model and the full information model. We also compare the optimal and myopic policies for the additive and multiplicative models. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007