随机布阵条件下同时数字多波束干扰优化设计方法

针对现有方法普遍存在的波束形成算法效率低、难以形成多频点多方向的同时多波束干扰、不适用于随机布阵条件下的波束形成等缺点,提出了一种基于二阶锥规划(SOCP,Second-Order Cone Programming)理论的同时数字多波束干扰形成方法。首先,给出了在随机布阵条件下干扰多波束优化设计问题的数学描述;其次,以范数准则为例,将随机布阵条件下干扰多波束设计问题的解析形式转化为相应的SOCP形式;再次,利用现有的原-对偶内点算法工具箱Se Du Mi或者CVX进行快速求解。最后,仿真结果表明该方法可以较好地解决随机布阵条件下的多频率多方向雷达目标同时多波束干扰优化设计问题。     

舰载机多机一体化机务保障调度研究

针对舰载机多机一体化机务保障调度问题,以出树、入树的形式描述实际保障过程中并行工序的约束关系,以最大保障完工时间和资源负载均衡性为目标,构建了舰载机多机一体化机务保障非线性多目标混合流水车间调度模型,并设计了一种结合基于Insert的动态邻域爬山搜索策略和并行工序的同步化修正的Memetic算法求解该模型。最后通过实例仿真验证了模型和所提算法的可行性和有效性。     

基于Virtools的洞库工程维护管理虚拟训练系统

为了解决洞库工程教学训练缺乏直观性和实践性的难题,利用Revit,Sketch Up和3D Max软件进行三维模型构建,以漫游中的基本图形变换和位置实时显示技术为例介绍了相关数学原理及Virtools编程实现过程,实现预定功能后发布了洞库工程维护管理虚拟训练系统。该虚拟训练系统具有功能演示、虚拟漫游、虚拟施工、维护管理虚拟训练和考核评估等功能,可以让学员身临其境地学习洞库工程维护管理的相关知识,有效地提高了教学效果。     

Balancing stability and efficiency in team formation as a generalized roommate problem

The assignment of personnel to teams is a fundamental managerial function typically involving several objectives and a variety of idiosyncratic practical constraints. Despite the prevalence of this task in practice, the process is seldom approached as an optimization problem over the reported preferences of all agents. This is due in part to the underlying computational complexity that occurs when intra-team interpersonal interactions are taken into consideration, and also due to game-theoretic considerations, when those taking part in the process are self-interested agents. Variants of this fundamental decision problem arise in a number of settings, including, for example, human resources and project management, military platooning, ride sharing, data clustering, and in assigning students to group projects. In this article, we study an analytical approach to “team formation” focused on the interplay between two of the most common objectives considered in the related literature: economic efficiency (i.e., the maximization of social welfare) and game-theoretic stability (e.g., finding a core solution when one exists). With a weighted objective across these two goals, the problem is modeled as a bi-level binary optimization problem, and transformed into a single-level, exponentially sized binary integer program. We then devise a branch-cut-and-price algorithm and demonstrate its efficacy through an extensive set of simulations, with favorable comparisons to other algorithms from the literature.     

搜索路径给定时的搜索对策问题及其应用

搜索路径给定时的最优搜索方案问题,也可以理解为是关于搜索者和目标的二人对策问题,主要讨论了当搜索路径给定时的单个搜索者和单个目标的搜索对策问题。首先根据问题的特点,利用动态规划和迭代的方法,确定关于目标逃逸路径混合策略的最优分区,证明该分区是多面体凸集;针对目标不同逃逸路径的分区,求出搜索者的最大期望收益,再将问题转化为二人有限零和对策,计算出搜索者的支付矩阵,确定最优搜索策略。最后结合海军护航行动,对我舰载直升机搜索小型海盗船进行分析和计算,说明搜索路径给定时的最优搜索对策对于双方的资源分配和提高搜索效率具有一定的应用价值。     

一类非线性系统的自适应模糊反推近似滑模控制

针对一类含有未知非线性函数项和外界干扰的不确定纯反馈非线性系统,提出了一种自适应模糊反推近似滑模变结构控制方法。采用中值定理和隐函数定理使未知非仿射输入函数拥有显式的控制输入,利用模糊系统逼近未知非线性函数,动态面控制技术解决了反推设计中出现的"微分爆炸"问题。所提出的自适应近似滑模控制方案削弱了传统滑模控制中的抖振现象。从理论上证明了所设计的控制器能够保证闭环系统所有信号半全局一致终结有界。仿真算例验证了算法的有效性。     

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     

滑模控制的新型双幂次组合函数趋近律

提出一种基于双幂次组合函数趋近律的新型滑模控制方案。与现有的快速幂次或双幂次趋近律相比,具有更快的收敛速度,同时还保持了全局固定时间收敛特性,收敛时间上界与滑模初值无关。当系统存在有界扰动时,能够使滑模变量在有限时间内收敛到稳态误差界内,同时其稳态误差要小于现有方法的。仿真实验验证了该方法的有效性及理论分析的正确性。     

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。     

The burglar problem with multiple options

We consider the burglar problem in which a burglar can either retire or choose among different types of burglaries, with each type having its own success probability and reward distribution. Some general structural results are established and, in the case of exponentially distributed reward distributions, a solution technique is presented. The burglar problem's relationship to a stochastic knapsack problem with a random exponentially distributed knapsack capacity is shown. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 359–364, 2014