大型消防装备采购模式及全寿命期费用控制问题探析

大型消防装备采购模式存在的一些问题,影响了大型消防装备全寿命期的经费使用效益,导致大型消防装备的购置费用高而效率低,装备闲置和利用率不高,装备全寿命期费用控制效果较差,必须建立大型消防装备全寿命费用管理体系,提高大型消防装备投资的效率。     

联合补充博弈的费用分摊

就一个仓库、多个零售商,对联合订货费用函数的模型进行分析,给出了一个求解最佳订货周期的多项式时间的算法,且算法的时间复杂性为O（nlogn）。利用文献[8]中的技巧,给出了该库存博弈的核。     

在英语课堂教学中培养学生的跨文化非语言交际能力

非语言交际传递了人们交际活动中的大部分信息,在人际交流中具有举足轻重的地位。本文通过四类非语言交际行为（即体态语、副语言、客体语和环境语）在英语课堂教学中出现的典型案例,阐释其所传递的跨文化信息,提出英语教师应当提高自己对英语文化环境下常见的非语言交际行为的把握,在课堂教学过程中,帮助学生在学习英语语言的同时,掌握英语文化环境下的非语言交际行为的准确含义,并以此加深对语言材料的理解,准确掌握有关文化背景,提高跨文化交际能力。     

某型末制导炮弹偏流的分析与计算

针对某型激光半主动式末制导炮弹偏流问题,基于考虑末制导炮弹各个典型弹道飞行阶段的刚体弹道模型,通过仿真计算,分析该末制导炮弹偏流的基本特点;探讨偏流形成的原因,确定影响其大小的关键因素,并对计算偏流所需要的数值积分时间步长进行了探讨。有关结论对准确编拟末制导炮弹射表所需要的偏流有直接应用价值,对新型末制导炮弹的弹道设计有积极的指导意义。     

电磁辐射测量仪的抗干扰设计

简要介绍根据电磁辐射测量理论设计的一款电磁辐射测量仪,并在此基础上详细阐述各种抗干扰措施,包括软件和硬件相应的抗干扰设计。实验证明,该测量仪运行正常,抗干扰性能良好。     

基于手势交互的三维电子沙盘系统设计与实现

基于手势的人机交互方式可大大提高人对计算机系统的控制能力,实现人机自然融合。首先,简要分析了Leap Motion设备进行手势识别的特点,详细阐述了利用Unity3D构建三维电子沙盘的方法和流程,在此基础上提出了基于手势交互的三维电子沙盘系统集成技术框架;然后,设计了基于Leap Motion的手势识别方案和控制脚本的基本流程,最后搭建系统实例并进行测试。测试结果表明,通过Leap Motion可实现人手对沙盘系统的预定操作,为这种新型手势识别技术的应用提供了一定借鉴。     

一种基于蚁群算法的准动态防空武器分配算法

武器目标分配问题是一个典型的限制组合优化问题,旨在得到在整个防御阶段中针对目标函数的最优武器分配方案。分配算法主要分为静态和动态两大类。针对传统静态分配模型中存在的几点问题,提出了基于时间窗的准动态武器目标分配算法,该算法综合考虑拦截概率、拦截时间和武器耗费多个优化指标,并将该算法推广至多类防空武器的优化分配中。通过大量实验验证,该算法在性能、时间复杂度等方面均有较大优势,并且能较好地适应战场态势的变化,及时调整分配方案,具有很好的实用性。     

Network design for time‐constrained delivery

To meet customer demand, delivery companies are offering an increasing number of time‐definite services. In this article, we examine the strategic design of delivery networks which can efficiently provide these services. Because of the high cost of direct connections, we focus on tree‐structured networks. As it may not be possible to identify a tree‐structured network that satisfies all of the delivery guarantees, we allow these guarantees to be violated but seek to minimize the sum of the violations. We establish the complexity of the problem and exploit an empirically identified solution structure to create new neighborhoods which improve solution values over more general neighborhood structures. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Scheduling parallel machines with inclusive processing set restrictions

We consider the problem of assigning a set of jobs to different parallel machines of the same processing speed, where each job is compatible to only a subset of those machines. The machines can be linearly ordered such that a higher‐indexed machine can process all those jobs that a lower‐indexed machine can process. The objective is to minimize the makespan of the schedule. This problem is motivated by industrial applications such as cargo handling by cranes with nonidentical weight capacities, computer processor scheduling with memory constraints, and grades of service provision by parallel servers. We develop an efficient algorithm for this problem with a worst‐case performance ratio of + ε, where ε is a positive constant which may be set arbitrarily close to zero. We also present a polynomial time approximation scheme for this problem, which answers an open question in the literature. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

In this study, we illustrate a real‐time approximate dynamic programming (RTADP) method for solving multistage capacity decision problems in a stochastic manufacturing environment, by using an exemplary three‐stage manufacturing system with recycle. The system is a moderate size queuing network, which experiences stochastic variations in demand and product yield. The dynamic capacity decision problem is formulated as a Markov decision process (MDP). The proposed RTADP method starts with a set of heuristics and learns a superior quality solution by interacting with the stochastic system via simulation. The curse‐of‐dimensionality associated with DP methods is alleviated by the adoption of several notions including “evolving set of relevant states,” for which the value function table is built and updated, “adaptive action set” for keeping track of attractive action candidates, and “nonparametric k nearest neighbor averager” for value function approximation. The performance of the learned solution is evaluated against (1) an “ideal” solution derived using a mixed integer programming (MIP) formulation, which assumes full knowledge of future realized values of the stochastic variables (2) a myopic heuristic solution, and (3) a sample path based rolling horizon MIP solution. The policy learned through the RTADP method turned out to be superior to polices of 2 and 3. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010