The impact of component commonality on composite assembly policies

Assemble in Advance (AIA) policy reduces assembly cost due to advance planning, while Assemble to Order (ATO) policy eliminates assembly of excessive (more than demanded) units. The tradeoffs between the two policies have been studied in the past for single product environments. Moreover, it was shown that it is beneficial to employ AIA and ATO simultaneously. In this article, we study the employment of such a composite assembly policy in a multiproduct environment with component commonality. When common components are used, ATO may also enable us to benefit from the risk pooling effect. We provide important managerial insights such as: the multiperiod problem is myopic and changes in inventory levels due to the use of common components, and demonstrate the potential profit increase compared to other policies.© 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Optimal burn‐in procedure for periodically inspected systems

Burn‐in is a widely used method to improve the quality of products or systems after they have been produced. In this paper, we study burn‐in procedure for a system that is maintained under periodic inspection and perfect repair policy. Assuming that the underlying lifetime distribution of a system has an initially decreasing and/or eventually increasing failure rate function, we derive upper and lower bounds for the optimal burn‐in time, which maximizes the system availability. Furthermore, adopting an age replacement policy, we derive upper and lower bounds for the optimal age parameter of the replacement policy for each fixed burn‐in time and a uniform upper bound for the optimal burn‐in time given the age replacement policy. These results can be used to reduce the numerical work for determining both optimal burn‐in time and optimal replacement policy. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Modeling and analysis of a mixed‐model assembly line with stochastic operation times

We consider a mixed‐model assembly line (MMAL) comprised a set of workstations and a conveyor. The workstations are arranged in a serial configuration. The conveyor moves at a constant speed along the workstations. Initial units belonging to different models are successively fed onto the conveyor, and they are moved by the conveyor to pass through the workstations to gradually generate final products. All assembling tasks are manually performed with operation times to be stochastic. An important performance measure of MMALs is overload times that refer to uncompleted operations for operators within their work zones. This paper establishes a method to analyze the expected overload times for MMALs with stochastic operation times. The operation processes of operators form discrete time nonhomogeneous Markov processes with continuous state spaces. For a given daily production schedule, the expected overload times involve in analyzing the Markov processes for finite horizon. Based on some important properties of the performance measure, we propose an efficient approach for calculating the expected overload times. Numerical computations show that the results are very satisfactory. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Technical note: Worst‐case performance of power‐of‐two policies for serial inventory systems with incremental quantity discounts

This study presents power‐of‐two policies for a serial inventory system with constant demand rate and incremental quantity discounts at the most upstream stage. It is shown that an optimal solution is nested and follows a zero‐inventory ordering policy. To prove the effectiveness of power‐of‐two policies, a lower bound on the optimal cost is obtained. A policy that has a cost within 6% of the lower bound is developed for a fixed base planning period. For a variable base planning period, a 98% effective policy is provided. An extension is included for a system with price dependent holding costs. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

基于神经网络的离散变结构控制系统

系统研究了基于神经网络的离散变结构控制系统设计方法,提出了几种具体设计方案.神经网络的引入可以使滑模(变结构)控制具备学习与自适应能力,使控制信号得以柔化,从而能够减轻或避免困扰常规滑模控制器的抖振现象,改善控制效果.     

空对空多机协同攻击多个目标的战术决策研究

简要介绍多机协同攻击多目标的基本概念、战术决策、目标分配及攻击排序方法。最后用数字仿真（实例）验证该方法的有效性     

引战配合三维计算机图形仿真的新技术

介绍了一种研制高质量引战配合三维计算机图形仿真软件的新技术。在目前广泛流行的３２ 位Ｗｉｎｄｏｗ ｓ 操作平台 （Ｗｉｎｄｏｗ ｓ ９５ 和Ｗｉｎｄｏｗ ｓＮＴ） 上利用Ｏｐ ｅｎＧＬ开发了多用途导弹反武装直升机引战配合三维图形仿真软件３Ｄ－ ＭＵＭ。运行结果表明： 该软件具有导弹和目标几何造型逼真、形象生动、使用方便灵活、运行速度高等优点     

Banyan网的一类非阻塞特性及其在ATM交换机设计中的应用

Ｂａｎｙａｎ网具有结构简单、自寻址、硬件复杂度低等优点，因而被许多交换系统和多机系统作为基本互连网络，但其内阻塞特性限制了它的性能。对某些特定输入模式，Ｂａｎｙａｎ网是非阻塞的。本文讨论Ｂａｎｙａｎ网的一类非阻塞特性，说明它们在ＡＴＭ交换机设计中的应用——通过数据分布提高ＡＴＭ交换机的负载均衡能力，用更小的硬件代价实现多目广播功能。     

军事电子信息处理中的人工神经网络技术

本文首先分析了现代战场环境对军事电子系统智能信息处理的应用需求，然后对人工神经网络理论与技术在军事电子信息处理中的现实应用与潜在前景给出了一个较为详细的介绍与分析。着重介绍了神经网络在雷达、红外及声纳目标的检测、识别、多机动目标跟踪及武器系统的智能控制等方面的应用情况，力图展示神经网络用于军事电子信息处理的特色与优势。最后分析了人工神经网络技术发展与应用中存在的一些问题。     

用于态势估计的贝叶斯网络方法

态势估计系统需要对大量的不确定性知识进行处理,不确定性知识表示和推理是态势估计中的研究热点.利用贝叶斯网络技术,可以实现对不确定性知识的处理.为此讨论了贝叶斯网络理论,详细分析了态势估计的功能模型,提出事件检测是态势估计的核心和起点,研究了用于态势估计的贝叶斯网络的构建方法.该方法充分考虑贝叶斯网络的几项基本要素,可以解决态势估计领域中贝叶斯网络的构建问题.贝叶斯网络技术在态势估计领域具有广阔的前景,将极大地推动态势估计系统的发展.