任务驱动的一体化作战指挥信息系统高效协同技术

针对一体化网络中心战下各参与方作战指挥信息系统的异构性、自治性、多样性等特点给联合协同作战带来的问题,提出了任务驱动的一体化作战指挥信息系统高效协同技术。以作战目标为导向将各作战力量和资源按需聚合和自主协同,引入自主个体、虚拟任务共同体和虚拟任务执行体,构建一体化虚拟作战指挥环境,为各作战单位提供高效、协同、透明的一体化服务。分别从核心元素、系统框架分别介绍高效协同体系结构,结合陆军合成营指挥信息系统案例对高效协同技术各组成部分进行深入分析,验证该技术的可行性。     

基于防火墙技术的VPN over DSL

本文主要讨论了利用防火墙技术构筑VPN over DSL,实现高效、安全的企业级虚拟专业网络,着重讨论了防火墙技术中关键的安全标准Ipsec。     

21世纪武器装备技术保障新走向

高技术武器装备的迅猛发展呼唤着快速而高效的技术保障,在分析外军为迎接高技术武器装备挑战,依靠科技实施技术保障改革的基础上,探索了我军跨世纪装备技术保障建设新模式。     

基于重要性采样的空时分组码快速仿真系统设计

高效的仿真技术对研究提高军事通信的性能具有重要意义。针对传统的蒙特卡罗仿真时间长的问题,提出了基于重要性采样的空时分组码高效仿真方法,给出了仿真模型和实现流程。仿真和分析结果表明本方法在运行较少的时间内能够获得较好的误码性能。采用该高效仿真方法可以加快军事通信技术研究的进程。     

浅谈信息抽取技术的"四种形式"和"四种功能"

信息化战争离不开对信息的获取、筛选和利用,但面对大量的信息我们常常措手无策,信息抽取技术正好解决了这一难题。信息抽取是信息处理领域中一种新兴的技术。该技术通过抽取、过滤无关信息,使信息以用户关心的形式得以再组织,实现高效重组,利用计算机进行高效存储并加以利用。     

GFT中的向量编译技术

本文介绍了一个高效而简洁的编译程序GFT及其所使用的主要编译技术。     

战场电磁态势融合感知技术框架研究?

为了高效精确感知现代战场条件下的电磁态势,分析了战场电磁态势感知的需求,研究了基于高层信息融合的电磁态势融合感知技术框架。战场电磁态势融合感知技术框架面向异构信息综合处理和融合模型柔性控制,基于电磁实体序列识别形成观测态势,基于作战行动企图估计形成估计态势,基于电磁威胁预测评估形成预测态势,构建现代战场综合电磁态势图。研究表明基于融合理论的战场电磁态势融合感知技术框架具有适应性强、高效精确的特点。     

交换式网络中的虚拟局域网技术

介绍了交换式网络中的VLAN技术的概念、宣传方法、实施标准,以及VLAN技术与ATM、DHCP、组播等其他技术的关系,使人们能够灵活地应用VLAN技术,轻及和其他技术一起,构建和管理一个更可靠、安全、高效的交换式网络。     

“双碳”战略下绿色能源无人机的发展机遇和挑战

对绿色能源无人机这一新兴航空技术领域进行了综合评述,并讨论了未来发展机遇和挑战。首先,阐述了绿色能源无人机的发展现状,介绍了典型太阳能无人机、氢燃料电池无人机,分析了高效柔性薄膜太阳能电池、轻质高效氢燃料电池等绿色能源动力关键技术;然后,对“双碳”战略带来的机遇进行了分析;最后,探讨了绿色能源无人机技术发展面临的挑战,以及未来发展方向,为绿色能源飞行器技术领域的研究工作和关键技术攻关提供一定参考。综述表明,“双碳”战略已经提升到了国家战略层面,绿色装备需求迫切,绿色航空发展进程正在加速。兼顾长航时和大载荷的实用化技术、低成本快捷改装技术以及多种能源混合互补技术等将是推动绿色能源无人机未来发展的关键。     

色谱技术在金属有机化合物形态分析中的应用

气相色谱（ＧＣ）和高效液相色谱（ＨＰＬＣ）等色谱分离技术与原子光谱等元素选择性检测技术组合可以直接对金属,准金属和有机金属化合物进行化学形态伯分析和测定,这些系统的灵敏度大致在ｎｇ到ｐｇ水平。本文叙述了气相色谱和高效液相色谱与各种原子光谱检测系统的性能以及这些系统的最新发展动态。     

Multiobjective fractional programming duality theory

Results of Geoffrion for efficient and properly efficient solutions of multiobjective programming problems are extended to multiobjective fractional programming problems. Duality relationships are given for these problems where the functions are generalized convex or invex.     

Postoptimality analysis in integer programming by implicit enumeration: The mixed integer case

This paper develops a method for doing postoptimality analysis on the mixed integer programming problem. The proposed procedures form a natural adjunct to enumerative I.P. algorithms that are linear programming based, and they are designed, in effect, to capitalize on insights generated as the problem is initially solved to do subsequent analysis upon it. In particular, limited ranging analysis is possible on selected parameters, as is the efficient resolving of the problem following parameter changes.     

Towards finding global representations of the efficient set in multiple objective mathematical programming

We propose and justify the proposition that finding truly global representations of the efficient sets of multiple objective mathematical programs is a worthy goal. We summarize the essential elements of a general global shooting procedure that seeks such representations. This procedure illustrates the potential benefits to be gained from procedures for globally representing efficient sets in multiple objective mathematical programming. © 1997 John Wiley & Sons, Inc.     

The parallel replacement problem with demand and capital budgeting constraints

A generalized parallel replacement problem is considered with both fixed and variable replacement costs, capital budgeting, and demand constraints. The demand constraints specify that a number of assets, which may vary over time, are required each period over a finite horizon. A deterministic, integer programming formulation is presented as replacement decisions must be integer. However, the linear programming relaxation is shown to have integer extreme points if the economies of scale binary variables are fixed. This allows for the efficient computation of large parallel replacement problems as only a limited number of 0–1 variables are required. Examples are presented to provide insight into replacement rules, such as the “no‐splitting‐rule” from previous research, under various demand scenarios. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 40–56, 2000     

求解整数规划问题的一个搜索方法

本文整数规划问题给出一种搜索方法,它类似于求解连续变量优化问题的迭代方法,从一个好的初始可行解出发,寻找一个搜索方向,沿着这个方向求出改进的可行解,然后又开始下一次迭代。此方法简单易行,可以求出问题的最优解或近似最优解,对于整数线性规划问题和整数非线性规划问题的求解都适用,并且容易推广到求解大规校整数线性规划问题。文中附有计算例子,说明方法是有效的。     

未知最优值线性规划的修正 Karmarkar算法

本文对未知最优值的Karmarkar型线性规划,得到了一种复杂性为O(n~(3.5)L)的修正Karmarkar 算法;通过讨论加边矩阵和秩1修正矩阵的LDL~T 分解,得到了一种计算Q—斜投影的有效方法。最后,从理论上分析了算法的收敛性和复杂性。     

Two machine flow shop scheduling problems with sequence dependent setup times: A dynamic programming approach

This paper considers the two different flow shop scheduling problems that arise when, in a two machine problem, one machine is characterized by sequence dependent setup times. The objective is to determine a schedule that minimizes makespan. After establishing the optimally of permutation schedules for both of these problems, an efficient dynamic programming formulation is developed for each of them. Each of these formulations is shown to be comparable, from a computational standpoint, to the corresponding formulation of the traveling salesman problem. Then, the relative merits of the dynamic programming and branch and bound approaches to these two scheduling problems are discussed.     

Scheduling to minimize the total compression and late costs

We consider a single-machine scheduling model in which the job processing times are controllable variables with linear costs. The objective is to minimize the sum of the cost incurred in compressing job processing times and the cost associated with the number of late jobs. The problem is shown to be NP-hard even when the due dates of all jobs are identical. We present a dynamic programming solution algorithm and a fully polynomial approximation scheme for the problem. Several efficient heuristics are proposed for solving the problem. Computational experiments demonstrate that the heuristics are capable of producing near-optimal solutions quickly. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 67–82, 1998     

The many-product cargo loading problem

An algorithm, based upon dynamic programming, is developed for a class of fixed-cost cargo loading problems. The problems can be formulated as integer programming problems, but cannot be efficiently solved as such because of computational difficulties. The algorithm developed has proved to be very efficient in an actual operations research study involving over 500 different cargo items, more than 40 possible stops and several types of transportation vehicles. A numerical illustration is provided.     

A generalized recursive algorithm for a class of non-stationary regeneration (scheduling) problems

Recent efforts in the field of dynamic programming have explored the feasibility of solving certain classes of integer programming problems by recursive algorithms. Special recursive algorithms have been shown to be particularly effective for problems possessing a 0–1 attribute matrix displaying the “nesting property” studied by, Ignall and Veinott in inventory theory and by Glover in network flows. This paper extends the class of problem structures that has been shown amenable to recursive exploitation by providing an efficient dynamic programming approach for a general transportation scheduling problem. In particular, we provide alternative formulations lor the scheduling problem and show how the most general of these formulations can be readily solved vis a vis recursive techniques.