线性调频基带数字产生的关键技术研究

介绍超宽带线性调频信号基带的数字产生方法及其实现技术。首先对线性调频信号的两种主要数字产生方法进行了简要阐述和比较，然后根据波形存储直读法提出了一种超宽带线性调频信号产生方案，分析了基带数字产生的主要关键技术，并进行了系统实现和测试。测试结果表明本文所提出的方法是可行的。     

基于黑板模型的分布式协同任务决策方法研究

基于黑板模型的分布式指挥控制网络为未来复杂环境下海战中多平台间的高效协同提供了新思路,通过构建应用于多航母群联合海战的分布式协同网络,对多航母群联合海战下的系统负载进行了研究,建立了一种多平台任务决策的数学模型,采用嵌套遗传算法进行了仿真求解,得到了理想的任务决策方案。最后对由于目标函数中内部负载权重系数不同取值所引起的不同任务决策结果进行了比较,验证了将基于黑板模型的分布式协同网络应用于多航母海战协同决策的科学性,为分布式海战协同决策网络的后续研究工作奠定了基础。     

符号执行火控系统诸元解算程序测试用例生成技术

火控系统作为各种武器装备的中枢和大脑,控制着武器系统的运转,其有效性直接关系着射击的成败甚至武器系统的综合效能。诸元解算程序是将各种输入条件依据弹道模型经过多次迭代转换为射击诸元,由于其复杂性,当前软件测试用例只是在几个关键点上进行校验,很难覆盖程序所有分支和路径,存在着测试不充分。针对这个问题,提出了一种基于符号执行的用例自动生成技术,结合解弹道方程组约束条件和程序分支控制变量使用符号执行框架内能够得到覆盖所有可能的执行路径,从而保证测试的充分性。     

A risk function for the stochastic modeling of electric capacity expansion

We present a stochastic optimization model for planning capacity expansion under capacity deterioration and demand uncertainty. The paper focuses on the electric sector, although the methodology can be used in other applications. The goals of the model are deciding which energy types must be installed, and when. Another goal is providing an initial generation plan for short periods of the planning horizon that might be adequately modified in real time assuming penalties in the operation cost. Uncertainty is modeled under the assumption that the demand is a random vector. The cost of the risk associated with decisions that may need some tuning in the future is included in the objective function. The proposed scheme to solve the nonlinear stochastic optimization model is Generalized Benders' decomposition. We also exploit the Benders' subproblem structure to solve it efficiently. Computational results for moderate‐size problems are presented along with comparison to a general‐purpose nonlinear optimization package. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:662–683, 2001     

Scheduling jobs and maintenance activities on parallel machines

Most machine scheduling models assume that the machines are available all of the time. However, in most realistic situations, machines need to be maintained and hence may become unavailable during certain periods. In this paper, we study the problem of processing a set of n jobs on m parallel machines where each machine must be maintained once during the planning horizon. Our objective is to schedule jobs and maintenance activities so that the total weighted completion time of jobs is minimized. Two cases are studied in this paper. In the first case, there are sufficient resources so that different machines can be maintained simultaneously if necessary. In the second case, only one machine can be maintained at any given time. In this paper, we first show that, even when all jobs have the same weight, both cases of the problem are NP-hard. We then propose branch and bound algorithms based on the column generation approach for solving both cases of the problem. Our algorithms are capable of optimally solving medium sized problems within a reasonable computational time. We note that the general problem where at most j machines, 1 ≤ j ≤ m, can be maintained simultaneously, can be solved similarly by the column generation approach proposed in this paper. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 145–165, 2000     

分布式虚拟环境中环境信息动态更新研究

环境信息动态更新是分布式虚拟环境的一个主要特点,如何使环境信息更新更活跃、更反应实际情况,一直是分布式虚拟环境研究的重点。在典型的分布式交互环境中,环境信息动态更新是基于协议数据单元(PDU),它不提供数据可靠性传输保证。如何保证分布式环境中各结点环境信息一致性,本文提出了一种信息校验和协议,它通过极少的信息传输就可保证各结点环境信息高度一致。文中定义了保证分布式环境信息动态一致性更新的协议数据单元,并在试验环境中证明了协议的可靠性。     

An exact branch‐and‐price algorithm for multitasking scheduling on unrelated parallel machines

We consider the multitasking scheduling problem on unrelated parallel machines to minimize the total weighted completion time. In this problem, each machine processes a set of jobs, while the processing of a selected job on a machine may be interrupted by other available jobs scheduled on the same machine but unfinished. To solve this problem, we propose an exact branch‐and‐price algorithm, where the master problem at each search node is solved by a novel column generation scheme, called in‐out column generation, to maintain the stability of the dual variables. We use a greedy heuristic to obtain a set of initial columns to start the in‐out column generation, and a hybrid strategy combining a genetic algorithm and an exact dynamic programming algorithm to solve the pricing subproblems approximately and exactly, respectively. Using randomly generated data, we conduct numerical studies to evaluate the performance of the proposed solution approach. We also examine the effects of multitasking on the scheduling outcomes, with which the decision maker can justify making investments to adopt or avoid multitasking.     

多阶段传感器-武器联合任务管理方法

针对动态环境下的传感器-武器联合任务管理问题展开研究。根据在动态作战过程中出现的有效新目标、有效空闲传感器和武器数量设定阶段门限,以决定进入下一阶段的时机,从而构建多阶段的作战过程。从打击方案质量及系统响应时间的角度出发,分析构建分布式作战体系对系统作战效能的影响,使系统在每个任务管理阶段可以决定响应流程。通过仿真实验验证了所构建的分布式作战体系与设定的阶段门限可以明显提升系统的作战效能。     

基于云计算的航天发射场业务网络体系架构

随着信息技术的不断发展,网络信息系统正不断向云计算、大数据不断演进。本文针对当前航天发射场网络体系存在的不足,结合信息技术发展趋势,提出了基于云计算的航天发射场网络体系架构设计。同时,结合航天发射场网络体系架构现状和实际,提出了首先实现发射场中心数据处理能力云化,再逐步实现发射场装备终端云化的演进策略,最终实现无中心化的分布式网络体系架构,将为有效解决航天业务信息系统体系弹性差、体系对抗能力弱等突出问题提供可选方案。     

分兵集火、凡船皆战——浅析美军“分布式杀伤”概念

通过梳理美军"分布式杀伤"概念的提出背景、提出过程、内涵意义,阐述了"分布式杀伤"的三条制胜之道,即符合海战客观环境、符合科技进步方向、符合战争演变趋势。此外,文章还分析了"分布式杀伤"实际执行过程中的几大难点和缺陷,包括指挥控制问题、舰船能力问题、成本和后勤补给问题、防御有效性问题。