不可预见作战下排弹抢修力量编配分析

在资源有限的情况下,综合考虑某一区域不同机场之间的相互关系,从整体的角度合理分配排弹抢修资源,可以大幅提升区域内军队机场阵地的战场排弹抢修能力.本文通过建立数学模型,从整体的角度出发,分析区域内各机场的排弹抢修资源分配问题:首先,针对不可预见作战带来的新挑战,提出了新的机场排弹抢修作业流程,引出排弹抢修力量分配所面临的...     

SpaceWire网络热点通信模式的缓存资源分配算法

基于SpaceWire网络在热点通信模式下的工作特点,研究缓存资源的分配算法。给出均匀通信模式和热点通信模式的释义;推导网络路由节点的满负荷概率和平均延时的解析方法,计算网络中的关键通信节点;再给出SpaceWire网络缓存资源分配算法。利用Opnet网络仿真平台建立SpaceWire通信模型,仿真了不同通信模式中采用缓存优化策略前后的关键性能指标。研究结果表明:在热点通信模式状态下,该缓存资源分配算法在保证总资源一定的前提下,网络系统的平均延时降低,优化了SpaceWire网络性能。     

伺服机构故障下基于线性规划的运载火箭姿控系统重构控制

发动机伺服机构故障给新一代运载火箭姿控系统的可靠性和安全性带来挑战,亟须开展重构控制策略研究。针对这一问题,提出一种基于线性规划的摆角重构控制分配方法。将伺服机构故障下的摆角分配问题转化为1范数单目标有约束优化问题,进而转化为标准的线性规划模型,采用单纯形法进行求解。仿真结果表明,所提出的线性规划法能够实现伺服机构故障下姿控系统的完全重构,各摆角均未达到饱和值,表明了方法的有效性。     

相依目标群状态转移概率矩阵的特性及其应用

本文对相依目标群的状态转移概率矩阵的性质进行了深入的分析,得到了若干重要结论,并在此基础上讨论了相依目标群系统的火力分配模型     

一种面向分布式寄存器文件的VLIW调度新策略

新一代面向密集计算的高性能处理器普遍采用分布式寄存器文件来支撑ALU阵列,并通过VLIW开发指令级并行.面向分布式寄存器文件的编译成为新兴的研究热点,在斯坦福大学的kernelC编译器ISCD中最早提出了面向分布式寄存器的VLIW调度问题,在该领域处于领先水平,但是没有解决重负载下的分布式寄存器分配问题,使应用编程受到极大限制.在其基础上提出了一种新的VLIW调度策略,实验结果表明能够很好地解决重负载下的分布式寄存器分配问题.     

车载多接入边缘网络中联合资源分配和动态任务卸载方案

针对车联网中车辆移动速度过快产生的任务卸载失败问题,设计了一个有效的任务卸载风险评估模型,并提出了联合资源分配的动态任务卸载方案。将时间、能耗和风险共同建模为系统效用,通过联合优化卸载决策、资源分配来最大化系统效用。优化问题被公式化为混合整数非线性规划,在给定卸载决策的情况下,利用凸优化技术解决计算资源分配问题,功率分配通过分式规划技术来优化。仿真分析了车辆移动性对系统效用的影响,证明了所提方案的合理性。     

并行面向对象数据库中的数据放置

针对并行面向对象数据库的特点,结合异步并行查询执行策略,提出了一种基于对象类的混合式数据放置策略,它包括两个部分:混合式数据划分策略和基于对象类的数据分配策略     

Dynamic routing of prioritized warranty repairs

Recent years have seen a strong trend toward outsourcing warranty repair services to outside vendors. In this article we consider the problem of dynamically routing warranty repairs to service vendors when warranties have priority levels. Each time an item under warranty fails, it is sent to one of the vendors for repair. Items covered by higher priority warranty receive higher priority in repair service. The manufacturer pays a fixed fee per repair and incurs a linear holding cost while an item is undergoing or waiting for repair. The objective is to minimize the manufacturer's long‐run average cost. Because of the complexity of the problem, it is very unlikely that there exist tractable ways to find the optimal routing strategies. Therefore, we propose five heuristic routing procedures that are applicable to real‐life problems. We evaluate the heuristics using simulation. The simulation results show that the index‐based “generalized join the shortest queue” policy, which applies a single policy improvement step to an initial state‐independent policy, performs the best among all five heuristics. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

战役野战油库油料输送力量优化分配研究

如何科学、合理分配战役野战油库油料输送力量是战时油料保障必须面临的一个实际问题。首先根据战役野战油库运油车分配模型得到一个运油车初始分配方案,然后运用计算机模拟技术对分配方案进行模拟,并根据模拟结果不断调整,直至得到优化的分配方案,为制定战役野战油库油料输送计划提供决策依据。     

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources,with application to COVID-19

Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.