对空观察哨情报融合

在得到对空观察哨直接观测信息的基础上,对目标可能航向进行二次外推,并利用效用函数综合评估法对目标相关性进行检验,完成对目标信息的融合,解决了观察哨情报数据关联和航迹外推问题.仿真及试验结果表明该方法用于防空观察哨情报融合是可行的,其结果分析的应用能指导观察哨训练和战时观察哨的配置.     

用科学发展观指导部队基层建设的实践与思考

从科学发展观的基本内涵出发,针对基层部队建设中存在的普遍问题,从全面建设、统筹规划、保持创新三个方面进行了论证,回答了科学发展观是指导部队基层建设的灵魂这个重大问题。     

On valuing appreciating human assets in services

This paper derives optimal policies for when to hire, train, and lay off employees in service organizations when worker productivity appreciates deterministically or stochastically under constant, monotonic, and cyclic service demand. The model, an extension of the machine replacement problem from the engineering economy literature, uses infinite horizon linear programming to produce optimal personnel planning strategies and dual prices that characterize the workforce's economic value. The effect of employee attrition is also considered. In its valuation of human assets, unlike pure accounting approaches that only try to measure, this paper proposes an approach to capture the interaction between firm decisions pertaining to human resources and human resource value. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

一种有效的XML-TO-SQL查询翻译优化算法

在研究XML数据处理问题上,XML查询与SQL查询的转换是一重要论题。在常规XML-TO-SQL查询转换算法基础上,分析了“翻译后优化”和“直接优化”两种不同的查询转换策略,提出了一种将Xpath路径表达式直接优化成SQL的算法。该算法将XML-TO-SQL查询转换分为两个主要阶段:预处理阶段和运行时翻译阶段。预处理阶段通过识别“双射映像”,计算“最小可辩识祖先”进行翻译前准备;运行时翻译则利用预处理阶段的结果进行路径约简。两个阶段的协作使得算法整体效率得以提高,达到翻译优化的目的。根据大数据量查询翻译对比实验的结果,该算法优于一些典型的传统翻译算法譬如Silk-Route、Xperanto等。     

基于Dijkstra算法的水平航迹规划

战术飞行任务的航迹规划是依靠地形信息和敌情信息,在某些约束条件下,找出作战飞机从起飞点到目标突防生存概率最大、航程最短的飞行轨迹的过程。采用简易方法建立了威胁模型,用Dijkstra算法实现了作战飞机整体最优水平航迹解算,并给出了具体算例,验证了算法的有效性和实用性。     

浅谈在营区规划中对营区文化的塑造

当前在军队工程建设中,对营区规划的主导思想已形成基本一致的认识,但多从物质技术层面去理解,就营区规划单位而言,尚没有广泛认识到营区文化也是规划中的重要内容以及在营区现代化建设中起着不可替代的作用。本文针对此情况重点论述了营区文化的主要内容和重要作用,并提倡通过对营区空间形态的创造来塑造有特色的营区文化,最终创造出一个充满凝聚力的,有利于长期发展的营区环境。     

Balancing and optimizing a portfolio of R&D projects

A mathematical formulation of an optimization model designed to select projects for inclusion in an R&D portfolio, subject to a wide variety of constraints (e.g., capital, headcount, strategic intent, etc.), is presented. The model is similar to others that have previously appeared in the literature and is in the form of a mixed integer programming (MIP) problem known as the multidimensional knapsack problem. Exact solution of such problems is generally difficult, but can be accomplished in reasonable time using specialized algorithms. The main contribution of this paper is an examination of two important issues related to formulation of project selection models such as the one presented here. If partial funding and implementation of projects is allowed, the resulting formulation is a linear programming (LP) problem which can be solved quite easily. Several plausible assumptions about how partial funding impacts project value are presented. In general, our examples suggest that the problem might best be formulated as a nonlinear programming (NLP) problem, but that there is a need for further research to determine an appropriate expression for the value of a partially funded project. In light of that gap in the current body of knowledge and for practical reasons, the LP relaxation of this model is preferred. The LP relaxation can be implemented in a spreadsheet (even for relatively large problems) and gives reasonable results when applied to a test problem based on GM's R&D project selection process. There has been much discussion in the literature on the topic of assigning a quantitative measure of value to each project. Although many alternatives are suggested, no one way is universally accepted as the preferred way. There does seem to be general agreement that all of the proposed methods are subject to considerable uncertainty. A systematic way to examine the sensitivity of project selection decisions to variations in the measure of value is developed. It is shown that the solution for the illustrative problem is reasonably robust to rather large variations in the measure of value. We cannot, however, conclude that this would be the case in general. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 18–40, 2001     

The selection allocation problem

The Selection Allocation Problem (SAP) is a single period decision problem which involves selecting profit‐maximizing (or cost‐minimizing) activities from various distinct groups, and determining the volume of those activities. The activities in each group are selected subject to the availability of that group's resource, which is provided by either pooling or blending raw inputs from several potential sources. Imbedded in the decision process is the additional task of determining how much raw input is to be allocated to each group to form the resource for that group. Instances of this problem can be found in many different areas, such as in tool selection for flexible manufacturing systems, facility location, and funding for social services. Our goal in this paper is to identify and exploit special structures in the (SAP) and use those structures to develop an efficient solution procedure. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 707–725, 1999     

VORONOI图的无人机航路快速初始规划

在分析VORONOI图的性质与威胁代价函数的基础上,针对航路的初始规划提出了一种先局部优化后进行全局优化的算法,从而避免在航路全局优化时陷入局部极小点的危险.通过对一个简单算例的分析,阐述了这种规划方法的合理性和快速性,给出了其对应的伪代码.它可对其他各种航路规划算法的边界条件进行初始预处理,快速确定初始可选航路集的解,缩短航路规划的时间;针对某阵地航路规划的仿真结果表明了该算法的有效性,初始的航路集有效地避开了威胁配置较密集的地方,同时尽量以较短的航路接近目标.     

从《中导条约》的失效看未来国际军控走向

《美苏消除两国中程导弹和中短程导弹条约》的失效重创了本就脆弱的国际军控体系，对美俄战略稳定和全球军事安全带来消极影响，国际军控合作和全球军事安全迫切需要重构新的军控体系。本文立足当前国际军控现状，在分析美俄“退约”背后各方战略考量及国际军控面临的挑战，如“美国优先”理念下的霸权主义和单边主义、国际军控体系自身的脆弱性和局限性和新军事革命给全球安全增添新的变量的基础上，提出了“构建人类命运共同体”理念凝聚全球安全共识、以大国责任和义务为基础构建多层次军控体系和以多边军控体系循序推进国际军控进程等措施和建议，以期为推动国际军控合作，建立更为公平、合理、有效的国际军控体系做出贡献。