改进Dijkstra算法在大型城市轨道交通网计价系统中的应用

随着城市地铁建设的迅猛发展,国内众多城市地铁线路均已实现网络化运营。考虑到地铁票价制定的公益性,目前国内大部分城市均以最短路径或最少车站的方式计算线网两车站间的票价。以传统的Dijkstra算法为基准,对传统的Dijkstra算法进行改进,分别采用传统Dijkstra算法和改进Dijkstra算法对长沙地铁1～5号线线网最短距离行走路线进行测算。结果表明,改进后的Dijkstra算法不仅有效地提高了算法的时效性,克服了传统算法时间冗长的缺陷,在一定程度上消除了线路之间累积的误差且提高了线网的可延展性。     

点邻域尺度差异描述的点云配准算法

针对传统特征描述符计算复杂度高、配准精度低的问题,提出一种基于不同尺度点邻域特征信息差异的点云配准算法。在特征描述符方面,对关键点选取不同尺度的邻域空间,计算各尺度空间之间的特征值归一化向量差异和法向量夹角,建立点邻域尺度差异描述符,特征描述符计算简单且节省时间。在关键点选取方面,根据曲面形状指数设计了一种寻找关键点的方法,提取的点具有很好的代表性。在对应关系寻找方面,提出一种基于欧式距离的对应点二重筛选方法,找出对应点对集,设计了基于全局距离的全局最优点云变换矩阵求取方法。实验结果表明,点邻域尺度差异描述的点云配准算法具有良好的配准精度和稳健的噪声鲁棒性。     

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     

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。     

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.     

美军联合信息环境计划?

联合信息环境计划（ JIE）是美国国防部为了提高军事网络的效率、效能与安全性，而对其国防信息基础设施进行的整合与重构计划。对美军联合信息环境计划的动因、关键技术和政策挑战、实施路径、对美军的影响等进行了较为全面的介绍。     

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。     

基于路径规划的无人机飞行冲突解脱技术

在无人机与有人机共用空域时,随时可能发生飞行冲突,应当有一种可靠的冲突解脱技术,保证无人机的空域运行安全。为此,构建了基于正三角形栅格法的空域运行环境,改进了以往十字栅格环境规划动态路径的缺陷;提出了基于空间分割的改进蚁群算法,提高了算法的寻优性能与路径规划能力。最后结合ADS-B系统的工作原理,在利用卡尔曼滤波对ADS-B信息进行修正的基础上,设计了无人机冲突感知的技术方案,并用实时的路径重规划技术实现飞行冲突的解脱。最终的仿真实验验证了飞行冲突解脱技术方案的有效性,可为未来无人机的空域运行技术提供一定的理论参考。