Single‐commodity stochastic network design under demand and topological uncertainties with insufficient data

Stochastic network design is fundamental to transportation and logistic problems in practice, yet faces new modeling and computational challenges resulted from heterogeneous sources of uncertainties and their unknown distributions given limited data. In this article, we design arcs in a network to optimize the cost of single‐commodity flows under random demand and arc disruptions. We minimize the network design cost plus cost associated with network performance under uncertainty evaluated by two schemes. The first scheme restricts demand and arc capacities in budgeted uncertainty sets and minimizes the worst‐case cost of supply generation and network flows for any possible realizations. The second scheme generates a finite set of samples from statistical information (e.g., moments) of data and minimizes the expected cost of supplies and flows, for which we bound the worst‐case cost using budgeted uncertainty sets. We develop cutting‐plane algorithms for solving the mixed‐integer nonlinear programming reformulations of the problem under the two schemes. We compare the computational efficacy of different approaches and analyze the results by testing diverse instances of random and real‐world networks. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 154–173, 2017     

Sensor placement in active multistatic sonar networks

The idea of deploying noncollocated sources and receivers in multistatic sonar networks (MSNs) has emerged as a promising area of opportunity in sonar systems. This article is one of the first to address point coverage problems in MSNs, where a number of points of interest have to be monitored in order to protect them from hostile underwater assets. We consider discrete “definite range” sensors as well as various diffuse sensor models. We make several new contributions. By showing that the convex hull spanned by the targets is guaranteed to contain optimal sensor positions, we are able to limit the solution space. Under a definite range sensor model, we are able to exclude even more suboptimal solutions. We then formulate a nonlinear program and an integer nonlinear program to express the sensor placement problem. To address the nonconvex single‐source placement problem, we develop the Divide Best Sector (DiBS) algorithm, which quickly provides an optimal source position assuming fixed receivers. Starting with a basic implementation of DiBS, we show how incorporating advanced sector splitting methods and termination conditions further improve the algorithm. We also discuss two ways to use DiBS to find multiple source positions by placing sensors iteratively or simultaneously. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 287–304, 2017     

基于小弹性模量法的空间飞网构型优化设计

飞网构型设计对提高空间飞网系统的展开抓捕性能具有重要意义。用小弹性模量分析方法对空间飞网构型优化设计问题进行了研究。以绳网中内力分布均衡性为优化目标,选取飞网抛射过程中最大受力时刻为研究工况,赋予绳索单元极小弹性模量,进行静力学计算,并以变形后的结果为初始条件进行迭代分析。优化结果表明,绳网中的内力分布随迭代步数的增加而更趋于均匀。在不改变绳网拓扑结构的前提下,本文所建立的优化设计方法为空间飞网构型优化设计提供了一种参考途径。     

多核贝叶斯优化的模型决策树算法

构造模型决策树时超参数较多,参数组合复杂,利用网格搜索等调参方法将会消耗大量的时间,影响模型性能的提升。提出了一种多核贝叶斯优化的模型决策树算法,该算法为应对不同分类数据特性,采用三种高斯过程建模寻优,利用贝叶斯优化技术,选出最优的参数组合。实验结果表明,所提算法在参数寻优上要优于传统的模型决策树寻优方法,并且能够在迭代次数不多的情况下找到全局最优参数值,在一定程度上提升了算法的分类性能,节省了大量的调参时间。     

伞衣优化设计对群伞系统气动特性的影响分析

随着载人航天、深空探测等航天任务的蓬勃发展,航天器回收载荷质量大幅提高,以单具降落伞为功能核心的传统减速系统已不能满足大质量回收载荷日益提高的迫切要求,发展群伞减速着陆系统是实现大载重航天器高效减速和无损着陆要求的发展方向。本文采用数值模拟手段对群伞系统的气动特性开展仿真研究,结合环帆伞构型优化设计,分析了多种构型下群伞系统的气动特性。通过对仿真结果进行流场分析和数据对比发现,开窗/开缝设计既能够确保群伞系统具有良好的阻力特性,又能够维持群伞系统的工作稳定性,避免单伞之间由于受力而发生碰撞现象。采用数值仿真手段不仅可以提高降落伞研制效率,降低研发成本,也为设计人员掌握群伞系统的工作原理、促进降落伞设计理论发展提供了有力保证。     

悬臂式围护桩受力性状与内力传递特征试验

为研究悬臂式围护桩结构的内力、弯矩、位移和嵌固段的变化规律及特点,结合西宁火车站综合改造工程,对该深基坑支护结构在不同开挖工况条件下悬臂桩的受力性状与内力传递特征进行现场动态测试试验。试验结果表明:悬臂桩的受力特征与理论值有所差异,在实际设计中可对其在配筋方式、混凝土强度设计、嵌固段长度等方面进行优化。试验结果可以有效优化桩身设计,为复杂基坑在开挖过程中的支护结构受力及变形提供参考性依据。     

基于粒子群优化的观测站部署算法

针对红外观测站部署问题,在研究观测站位置对定位精度影响的基础上,提出了基于粒子群优化的观测站部署算法。首先对ECEF坐标系下的CRLB矩阵进行推导;然后将观测站优化部署问题抽象为非线性规划模型,并将红外传感器联合定位的CRLB作为目标函数;最后采用粒子群优化算法求解该模型,避免了传统的非线性规划算法需要求解目标函数梯度的难题。结果表明,本文的部署算法具有一定的理论依据和工程意义;可以为实际红外观测站的静态部署和动态部署提供参考。     

基于SWOT分析的警卫情报工作优化研究

当前,警卫情报工作的范围已经扩展到警卫实战、预警、决策、管理等各个方面,但从总体上看,警卫情报工作仍需进一步优化,以满足日益增长的警卫实践需求。针对警卫情报工作的特点,采用SWOT分析法对警卫情报工作的内外部条件进行客观分析,提出针对性的优化策略,以提升警卫情报工作能力。     

瞄准式战斗部瞄准策略研究

对不同的瞄准点,瞄准式战斗部对目标毁伤效果不同,为此提出了适用于瞄准式战斗部的瞄准策略,保证了对目标较高的毁伤概率和较好的毁伤效果,解决了起爆之前战斗部的定位问题。     

基于径向基代理模型的序列优化中自适应再采样策略

针对径向基插值代理模型样本点预测误差为零时无法获得误差函数进行序列再采样优化的问题,将样本点分布约束引入序列再采样过程,利用潜在最优解加速收敛性,提出一种适用于径向基插值代理模型序列优化的再采样策略,该策略兼顾仿真模型的输出响应特性与样本点的空间分布特性。仿真结果表明,使用该在采样策略后,算法寻优效率和精度均优于传统基于代理模型的优化方法,在对最优解进行有效预测的同时,能显著减少原始模型计算次数。