Multi‐period maintenance scheduling of tree networks with minimum flow disruption

We introduce a multi‐period tree network maintenance scheduling model and investigate the effect of maintenance capacity restrictions on traffic/information flow interruptions. Network maintenance refers to activities that are performed to keep a network operational. For linear networks with uniform flow between every pair of nodes, we devise a polynomial‐time combinatorial algorithm that minimizes flow disruption. The spiral structure of the optimal maintenance schedule sheds insights into general network maintenance scheduling. The maintenance problem on linear networks with a general flow structure is strongly NP‐hard. We formulate this problem as a linear integer program, derive strong valid inequalities, and conduct a polyhedral study of the formulation. Polyhedral analysis shows that the relaxation of our linear network formulation is tight when capacities and flows are uniform. The linear network formulation is then extended to an integer program for solving the tree network maintenance scheduling problem. Preliminary computations indicate that the strengthened formulations can solve reasonably sized problems on tree networks and that the intuitions gained from the uniform flow case continue to hold in general settings. Finally, we extend the approach to directed networks and to maintenance of network nodes. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

分布式计算机网络数据加密研究

针对C~3I 系统对分布式计算机网络数据加密的特定需求,重点对网络加密方式、密码装置、软件编程设计等核心问题进行了研究。可对数据加密总体设计与软件概要设计提供参考。     

基于制导武器的分布式半实物仿真系统研究

应导弹动态性能指标检验的迫切需求,开发了基于制导武器的分布式半实物仿真系统。充分利用仿真模型构建一体化思想,将整个半实物仿真系统按其功能划分成若干个网络节点,采用弹道仿真工作站集中式分布的星形结构进行分布式系统仿真。仿真软件借鉴Windows操作系统消息、事件驱动方式,采用客户/服务器运行机制,基于VC＋＋软件开发工具实现了半实物仿真系统中的数据采集、视景驱动的多线程开发,修正了视线角误差,从而确保了导弹动态性能检测精度;实现了导弹攻击过程可视化仿真,较准确地再现了制导武器在不同干扰条件下的攻击过程。     

某特种车辆TTCAN网络的静态调度设计

针对某特种车辆计算机控制系统对实时性的高要求,采用了TTCAN总线系统,为实现TTCAN系统的静态调度问题,提出了基于AL算法的改进算法——谐波周期算法,并通过MATLAB建立了系统的调度表。针对谐波周期算法的不足,结合该计算机控制系统的工作原理、信息传输的重要程度对静态调度表进行了适当的修改。通过与AL算法的对比分析,证实了改进的谐波周期算法在保证系统中周期型消息实时性能前提下,为非周期型信息获得了更大的传输带宽,又使系统信息传输的时间分配更加合理。     

分布式数据库数据同步技术研究

针对分布式数据库要求,在研究Oracle及相关系统的基础上,分析比较了几种数据同步技术方案的实现原理和优缺点,并讨论了其适用场合.     

基于分布式排队网络的防空战术协同模型

分析了多个防空火力单元的作战过程,将战术BM/C3的控制协调决策抽象为决策策略。建立了多个火力单元协同作战的排队网络模型,并运用SPN理论对排队网络的运行机制进行了强有力的描述,有效地体现了防空作战过程中的威胁评估、目标分配等战术决策过程。这将为建立大型复杂排队网络,模拟仿真战役层面防空作战过程奠定基础。     

防空监视网络传感器任务优先级的模糊评价方法

传感器任务优先级是传感器管理的重要依据。应用模糊推理技术的传感器任务优先级评价方法,基于所有融合航迹和识别数据,通过符号推理确定决策循环过程中执行的每个监视任务的优先级。首先确定了管理系统结构,建立了优先级决策树,给出了模糊推理规则,最后进行了仿真试验。试验结果说明了模糊评价方法在传感器管理应用中的有效性。     

Proactive release procedures for just‐in‐time job shop environments,subject to machine failures

In this paper, we consider just‐in‐time job shop environments (job shop problems with an objective of minimizing the sum of tardiness and inventory costs), subject to uncertainty due to machine failures. We present techniques for proactive uncertainty management that exploit prior knowledge of uncertainty to build competitive release dates, whose execution improves performance. These techniques determine the release dates of different jobs based on measures of shop load, statistical data of machine failures, and repairs with a tradeoff between inventory and tardiness costs. Empirical results show that our methodology is very promising in comparison with simulated annealing and the best of 39 combinations of dispatch rules & release policies, under different frequencies of breakdowns. We observe that the performance of the proactive technique compared to the other two approaches improves in schedule quality (maximizing delivery performance while minimizing costs) with increase in frequency of breakdowns. The proactive technique presented here is also computationally less expensive than the other two approaches. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

联合作战规划中资源调度算法研究

以联合作战为例建立任务和作战平台资源模型,通过多维动态列表规划算法(Multidimensional Dynamic List Scheduling,MDLS)进行任务-平台分配,对平台选择提出了两种不同的优先权计算方法,通过对案例求解比较了不同方法的结果.     

Case‐based reasoning and improved adaptive search for project scheduling

Most scheduling problems are notoriously intractable, so the majority of algorithms for them are heuristic in nature. Priority rule‐based methods still constitute the most important class of these heuristics. Of these, in turn, parametrized biased random sampling methods have attracted particular interest, due to the fact that they outperform all other priority rule‐based methods known. Yet, even the “best” such algorithms are unable to relate to the full range of instances of a problem: Usually there will exist instances on which other algorithms do better. We maintain that asking for the one best algorithm for a problem may be asking too much. The recently proposed concept of control schemes, which refers to algorithmic schemes allowing to steer parametrized algorithms, opens up ways to refine existing algorithms in this regard and improve their effectiveness considerably. We extend this approach by integrating heuristics and case‐based reasoning (CBR), an approach that has been successfully used in artificial intelligence applications. Using the resource‐constrained project scheduling problem as a vehicle, we describe how to devise such a CBR system, systematically analyzing the effect of several criteria on algorithmic performance. Extensive computational results validate the efficacy of our approach and reveal a performance similar or close to state‐of‐the‐art heuristics. In addition, the analysis undertaken provides new insight into the behaviour of a wide class of scheduling heuristics. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 201–222, 2000