防空导弹武器系统抢修性时间参数模型

抢修性作为武器系统的一种特性,与武器系统本身的结构、损伤及抢修人员、工具等许多因素有关。防空导弹武器系统组成复杂,抢修性度量困难。在分析抢修性概念模型的基础上,从抢修性函数着手,推导并建立了防空导弹武器系统抢修性参数模型,最后通过算例对模型进行了验证,为解决防空导弹武器系统抢修性量化难题提供了一种有效的途径。     

基于欧拉角观测模型的航天器姿态确定方法

针对基于乘性误差四元数的EKF姿态确定技术,系统研究了姿态敏感器常用的欧拉角观测模型,从两个方面证明了目前许多文献中所构造的欧拉角误差相对于误差四元数矢部的测量灵敏度矩阵存在缺陷,从理论上剖析了这一问题的成因,并推导了正确的测量灵敏度矩阵形式,数值仿真进一步验证了本文的结论。     

军事装备系统可靠性设计分析

军事装备系统是决定战争胜负的关键因素之一,装备系统的可靠性直接决定装备系统效能的发挥。军事装备系统的可靠性定量分析结果,是军事装备系统进行可靠性设计的重要依据。本文利用系统工程的理论,结合军事装备系统特殊要求,定量的分析了装备系统可靠性模型,提出了增强装备系统可靠性的设计方法。     

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。     

自适应网格交互多模型算法

研究和设计了一种模型集合自适应方法——自适应网格方法。并将其与交互多模型算法相结合,提出了自适应网格交互多模型(AGIMM)算法,它是一种变结构多模型算法。仿真显示它能有效地提高IMM估计器的费效比。     

物元理论在优选对地打击目标中的应用

优选对地打击目标是现代信息化战争条件下联合作战对地火力协调中心在计划火力时的首要任务。旨在从目标的重要性、可靠性、射击紧迫性及对其射击时自身被发现的机会四个因素入手,举例证明如何构造物元模型,做到定性与定量相结合,对于编制炮兵C4I系统计划火力软件具有一定的参考价值。     

一种性能驱动的时序规划方法

在超级计算机体系结构设计阶段 ,有必要进行时序规划 ,以尽早判断设计方案和性能指标的物理可实现性。提出一种性能驱动的时序规划方法 ,采用适于组件性能描述的时序性能模型 ,并按照线网权重分配路径延时余量 ,算法具有效率高、延时分配合理的优点     

火控雷达的仿真目标建模及实现

中外军队的实践证明 :模拟训练是一种最简便、成本低、效果好的训练方式。对于需要空情保障和训练成本高的雷达训练来说更是如此。探讨了火控雷达回波信号的模型建立及实施方案。     

A single‐period inventory placement problem for a serial supply chain

This article addresses the inventory placement problem in a serial supply chain facing a stochastic demand for a single planning period. All customer demand is served from stage 1, where the product is stored in its final form. If the demand exceeds the supply at stage 1, then stage 1 is resupplied from stocks held at the upstream stages 2 through N, where the product may be stored in finished form or as raw materials or subassemblies. All stocking decisions are made before the demand occurs. The demand is nonnegative and continuous with a known probability distribution, and the purchasing, holding, shipping, processing, and shortage costs are proportional. There are no fixed costs. All unsatisfied demand is lost. The objective is to select the stock quantities that should be placed different stages so as to maximize the expected profit. Under reasonable cost assumptions, this leads to a convex constrained optimization problem. We characterize the properties of the optimal solution and propose an effective algorithm for its computation. For the case of normal demands, the calculations can be done on a spreadsheet. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:506–517, 2001     

An integer programming model for the weekly tour scheduling problem

We study a workforce planning and scheduling problem in which weekly tours of agents must be designed. Our motivation for this study comes from a call center application where agents serve customers in response to incoming phone calls. Similar to many other applications in the services industry, the demand for service in call centers varies significantly within a day and among days of the week. In our model, a weekly tour of an agent consists of five daily shifts and two days off, where daily shifts within a tour may be different from each other. The starting times of any two consecutive shifts, however, may not differ by more than a specified bound. Furthermore, a tour must also satisfy constraints regarding the days off, for example, it may be required that one of the days off is on a weekend day. The objective is to determine a collection of weekly tours that satisfy the demand for agents' services, while minimizing the total labor cost of the workforce. We describe an integer programming model where a weekly tour is obtained by combining seven daily shift scheduling models and days‐off constraints in a network flow framework. The model is flexible and can accommodate different daily models with varying levels of detail. It readily handles different days‐off rules and constraints regarding start time differentials in consecutive days. Computational results are also presented. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 607–624, 2001.